# Music machine learning - Introduction

### Author: Philippe Esling (esling@ircam.fr)

In this course we will cover
1. A [first definition](#definition) on the concept of machine learning
2. An introduction to a simple problem of [linear regression](#regression)
3. An explanation on [model capacity and overfitting](#capacity)
4. An introduction to the [audio datasets](#audio) that we will use

<a id="definition"></a>
## Defining machine learning

In all natural process, there exists complex relations between sets $\mathcal{X} \mapsto \mathcal{Y}$. This can relate some objects with their names, or a cause to a consequence. In most cases, _we do not know the precise relations_ between these sets, all we have is _observations_ such as pairs $(x,y)$, composed of input data $x \in \mathcal{X}$, which have a corresponding expected output $y \in \mathcal{Y}$. The overarching goal of machine learning is to approximate such _unknown processes_ as a function $\mathcal{F}_{\theta}$, which _transforms_ input data $x$ into output data $y$.



Hence, machine learning aims to understand and model the relationship between some (usually complex and high-dimensional) inputs $\mathbf{x}\in\mathcal{X}\subset\mathbb{R}^{\mathcal{X}}$ and outputs $\mathbf{y}\in\mathcal{Y}\subset\mathbb{R}^{\mathcal{Y}}$, given by a set of data examples $\mathcal{D}=\left\{(x_1,y_1),\cdots,(x_N,y_N)\right\}$. This is achieved by defining a parametric model $f_{\mathbf{\theta}}\in\mathcal{F}$ inside a family of functions $\mathcal{F}$, which depends on parameters $\mathbf{\theta} \in \mathbf{\Theta}$ and that could approximate the underlying relationship. The _learning_ aspect refers to the adjustment of the parameters $\mathbf{\theta}$ in order to obtain the best approximation of the given task
$$
\begin{equation}
f_{\mathbf{\theta}}(\mathbf{x}) = \hat{\mathbf{y}}\approx \mathbf{y}.
\end{equation}
$$

To observe this idea in simple setups, we are going to use the `numpy` library and `matplotlib` for plotting. We also set some fixed random generator, to ensure reproducibility


```python
# Base imports
import numpy as np
import matplotlib.pyplot as plt
from helper_plot import prep_plots, finalize_plots, hdr_plot_style
rng = np.random.RandomState(1)
```

<a id="regression"></a>
## Simple learning problem

Imagine that a certain process somewhere follows the form of a quadratic relationship

$$
 y = a x^{2} + bx + c 
$$

In this case, all the **unknown parameters** are that of a polynomial model, therefore we have $\theta = \{a, b, c\}$. However, this is clearly an ideal (clean) case, whereas in natural observations, there might be some noise in our observations
$$
 y = a x^{2} + bx + c +\epsilon \quad \mbox{with} \quad \epsilon \in [-0.1, 0.1]
$$

An example of such noisy observations for different parameters is given below


```python
noise_level = 0.9
a, b, c = 3, 0, 1
# Generating 
x = np.linspace(0, 1, 100)
poly = np.poly1d([a, b, c])
epsilon = np.random.uniform(-noise_level,noise_level,x.shape)
y = poly(x) + epsilon
ax1, = prep_plots(["Simple learning problem"], fig_size=(10,8), fig_num=1)
ax1.scatter(x, y, color='green', s=50, marker='o', edgecolor='w', label="training samples")
finalize_plots([ax1], fig_title="")
#plt.xlim([-1, 2])
```

Now our main problem is that this function can follow different types of parameters


```python
params = [[3, 0, 1], [-2, 1, 0], [0.1, 1, 1]]
ax = prep_plots(["Problem 1", "Problem 2", "Problem 3"], fig_size=(20,6), fig_num=1)
# Generating 
x = np.linspace(0, 1, 100)
for p in range(len(params)):
    poly = np.poly1d(params[p])
    epsilon = np.random.uniform(-noise_level,noise_level,x.shape)
    y = poly(x) + epsilon
    ax[p].scatter(x, y, color='green', s=50, marker='o', edgecolor='k', label="training samples")
finalize_plots(ax, fig_title="Different observations")
```

In real-life settings, this function can also have different levels of noise, as exemplified in the following code.


```python
params = [3, 0, 1]
noise_levels = [0.1, 1.0, 8.0]
ax = prep_plots(["Problem 1", "Problem 2", "Problem 3"], fig_size=(20,6), fig_num=1)
# Generating 
x = np.linspace(0, 1, 100)
for p in range(len(noise_levels)):
    poly = np.poly1d(params)
    epsilon = np.random.uniform(-noise_levels[p],noise_levels[p],x.shape)
    y = poly(x) + epsilon
    ax[p].scatter(x, y, color='green', s=50, marker='o', edgecolor='w', label="training samples")
finalize_plots(ax, fig_title="Different amounts of noise")
```

To summarize, we will have some observations of a function, and we would like to optimize a function that gets as close as possible to the real function that generated this data. Here, we plot the real function and also _subsample_ our number of observations (having only a few points to find the corresponding function)


```python
# Generating the data and subsampling
x_all = np.linspace(0, 1, 100); x_plot = np.linspace(0, 1, 100)
rng.shuffle(x_all); x = np.sort(x_all[:10])
poly = np.poly1d([3,0,1])
# Adding some external
epsilon = np.random.uniform(-0.1,0.1,x.shape)
y = poly(x)+ epsilon
# We keep the standard deviation for later
nnstd = np.std(epsilon); lw = 2
ax1, = prep_plots(["Simple learning problem"], fig_size=(10,8), fig_num=1)
ax1.plot(x_plot, poly(x_plot), color='green', linewidth=4, label='true function')
ax1.scatter(x, y, color='green', s=50, marker='o', edgecolor='w', label="training samples")
finalize_plots([ax1], fig_title="")
```

To get a first grip on what machine learning does, we will rely on the `scikit-learn` library. This contains already coded models and learning procedure, that will allow us to _learn_ the parameters of this unknown function.

Here we already know that we want to use a `PolynomialFeatures` model to perfom `LinearRegression` and that this polynomial should be of degree 2.


```python
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import PolynomialFeatures
from sklearn.pipeline import make_pipeline
# Our data to fit
X = x[:, np.newaxis]
# Degree of our polynomial
degree = 2;
# Create our polynomial model for regression
model = make_pipeline(PolynomialFeatures(degree), LinearRegression())
# Fit the parameters of this model
model.fit(X, y)
```




    Pipeline(steps=[('polynomialfeatures', PolynomialFeatures()),
                    ('linearregression', LinearRegression())])



Now that we have trained the model, we can perform _predictions_ from it, meaning that we can infer the output of the function at values that we did not observe originally.


```python
# Inference points (not observed)
X_plot = x_plot[:, np.newaxis]
# Predict the values
y_plot = model.predict(X_plot)
# Compute the error of our model at observed points
Y_model_err = np.sqrt(np.mean(np.square(y-model.predict(X))))
# Plot the result
ax1, = prep_plots(["Trained model"], fig_size=(10,8), fig_num=1)
ax1.plot(x_plot, y_plot, color='red', linewidth=4, label='trained model')
ax1.scatter(x, y, color='green', s=50, marker='o', edgecolor='w', label="training samples")
finalize_plots([ax1], fig_title="")
print(f'Model error : {Y_model_err}')
```

<a id="capacity"></a>
## Understanding model capacity and selection


In real-life problem, we are aiming to find the parameters of a model, but we do not really know what is the _real_ function underlying this process. So what we can decide to select _any_ function of _any_ **capacity** (complexity of the function). One of the problem with that, is that if we have a too simple function, it will _underfit_ (it is not complex enough for our observations). On the opposite end, if we have a function which is too complex, it might be able to _fit through all training points exactly_ ... even though there is noise in our observations ! This is examplified in the following



We can observe this idea and play with it directly by trying to find a function approximating our previous observations with a polynomial function chosen to have a degree inside \([1,2,8]\).



```python
X_plot = x_plot[:, np.newaxis]
ax1, ax2 = prep_plots(["training error", "model generalization"], fig_size=(15,4), fig_num=1)
ax1.plot([1,8], [nnstd, nnstd], label="noise level")
ax2.scatter(x, y, color='orange', edgecolor='w', s=50, marker='o', label="training samples")
colors = ['blue', 'green', 'red']; labels = ['underfitting', 'good fit', 'overfitting']
axes_sub = prep_plots(labels, fig_size=(15,4), fig_num=2)
# Optimize different degree polynomials
for count, degree in enumerate([1,2,8]):
    model = make_pipeline(PolynomialFeatures(degree), LinearRegression())
    model.fit(X, y)
    Y_model_err = np.sqrt(np.mean(np.square(y-model.predict(X))))
    y_plot = model.predict(X_plot)
    ax1.scatter(degree, Y_model_err, s=50, marker="o", edgecolor='w', label=labels[count])
    ax2.plot(x_plot, y_plot, color=colors[count], linewidth=2,label=labels[count])
    ax2.set_ylim((0,4))
    axes_sub[count].scatter(x, y, color='orange', edgecolor='w', s=50, marker='o', label="Training samples")
    axes_sub[count].plot(x_plot, y_plot, color=colors[count], linewidth=2,label=labels[count])
    axes_sub[count].set_ylim((0,4))
finalize_plots(axes_sub, fig_title="Linear regression")
finalize_plots([ax1,ax2], fig_title="Linear regression")
```


Depending on the _capacity_ of the model, what we can observe is that

- `capacity too low   -> underfitting   : prediction variance >  noise variance`
- `adequate capacity  -> good fit       : prediction variance == noise variance`
- `capacity too high  -> overfitting    : prediction variance <  noise variance`


A similar example can be given for a classification problem in two dimensions as follows




<a id="audio"></a>
## Audio applications

In order to test our algorithms on audio and music data, we will work with several datasets that should be downloaded on your local computer first from this [link ](https://nuage.ircam.fr/index.php/s/FTsaaAMFV1jEwsk)

  |**Type**|*Origin*|
  |-------:|:---------|
  |**Classification**|[*MuscleFish*](http://knight.cis.temple.edu/~vasilis/Courses/CIS750/Papers/muscle_fish.pdf) dataset|
  |**Music-speech**|[*MIREX Recognition*](http://www.music-ir.org/mirex/wiki/2015:Music/Speech_Classification_and_Detection) set|
  |**Source separation**|[*SMC Mirum*](http://smc.inesctec.pt/research/data-2/) dataset|
  |**Speech recognition**|[*CMU Arctic*](http://festvox.org/cmu_arctic/) dataset|

**Unzip the file and place the `data` folder along with the other code folders**
For the first parts of the tutorial, we will mostly rely solely on the classification dataset. In order to facilitate the interactions, we provide the function `import_dataset` that will allow to import all audio datasets along the tutorials.

```Python
def importDataset(class_path, type):
    """
    Helper function to import datasets
    % class_path  : Path to the dataset (string)
    % type       : Type of dataset (string: 'classify', 'plain', 'metadata')
    """ 
    # Returns the data_struct structure with
    data_struct["filenames"]  # Cell containing the list of audio files
    data_struct["classes"]    # Vector of indexes assigning each file to a class
    data_struct["class_names"] % Cell of class names
    return data_struct
```
  
***

**_Exercise_**  

  1. Launch the import procedure  and check the corresponding structure
  2. Code a count function that prints the name and number of examples for each classes 

***


```python
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
from helper_data import import_dataset
# 0.1 - Import the classification dataset
class_path = 'data/classification';
data_struct = import_dataset(class_path, 'classification');
```

        - Importing dataset data/classification.
    



```python
#%% Q-0.1.2 - Count function to print the number of examples

######################
print(data_struct.keys())
k=0
for name in data_struct["class_names"]:
    counter=0
    for classn in data_struct["classes"]:
        if classn==k:
            counter+=1
    print(name+ " : "+ str(counter))
    k+=1
######################

```

    dict_keys(['filenames', 'classes', 'class_names'])
    altotrombone : 13
    telephone : 17
    percussion : 99
    animals : 9
    violinpizz : 40
    speech.female : 35
    violinbowed : 45
    oboe : 32
    bells : 7
    speech.male : 17
    laughter : 7
    tubularbells : 20
    crowds : 4
    cellobowed : 47
    water : 7
    machines : 11


### Preprocessing

We will rely on a set of spectral transforms that allow to obtain a more descriptive view over the audio information. As most of these are out of the scope of the machine learning course, we redirect you to a [signal processing course](https://ccrma.stanford.edu/~jos/sasp/) proposed by [Julius O. Smith](https://ccrma.stanford.edu/~jos/).  

The following functions to compute various types of transforms are given as part of the basic package, in the `helper_data.py` file  

  |**File**|*Transform*|
  |-------:|:----------|
  |`stft.m`       |[Short-term Fourier transform](https://en.wikipedia.org/wiki/Short-time_Fourier_transform)|
  |`fft2barkmx.m` |[Bark scale](https://en.wikipedia.org/wiki/Bark_scale) transform|
  |`fft2melmx.m`  |[Mel scale](https://en.wikipedia.org/wiki/Mel_scale) transform|
  |`fft2chromamx` |[Chromas vector](https://en.wikipedia.org/wiki/Harmonic_pitch_class_profiles)|
  |`spec2cep.m`   |[Cepstrum](https://en.wikipedia.org/wiki/Cepstrum) transform|
  |`cqt.m`        |[Constant-Q](https://en.wikipedia.org/wiki/Constant_Q_transform) transform|

In order to perform the various computations, we provide the following function, which performs the different transforms on a complete dataset.  

``` Python
def computeTransforms(data_struct)
    """ data_struct   : Dataset structure with filenames """
    return data_struct

# Returns the data_struct structure with
data_struct["spectrum_power"]     # Power spectrum (STFT)
data_struct["spectrum_mel"]       # Spectrum in Mel scale
data_struct["spectrum_chroma"]    # Chroma vectors
data_struct["spectrum_CQT"]       # Constant-Q transform
```


***

**Exercise**  

  1. Launch the transform computation procedure and check the corresponding structure
  2. For each class, select a random element and plot its various transforms on a single plot. You should obtain plots similar to those shown afterwards.
  3. For each transform, try to spot major pros and cons of their representation.
  
***


```python
# 0.2 - Pre-process the audio to obtain spectral transforms 
# (may take around a minute)
from helper_data import compute_transforms
data_struct = compute_transforms(data_struct);
```

        - Performing transforms.
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=66
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=466
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=316
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=158
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=79
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=40
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=320
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=160
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=80
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=287
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=144
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=72
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=36
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=275
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=138
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=69
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=487
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=282
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=141
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=71
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=279
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=262
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=430
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=215
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=108
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=54
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=361
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=181
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=448
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=224
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=112
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=56
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/pitch.py:153: UserWarning: Trying to estimate tuning from empty frequency set.
      warnings.warn("Trying to estimate tuning from empty frequency set.")
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=259
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=87
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=370
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=185
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=323
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=162
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=311
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=156
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=78
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=74
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=37
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=474
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=237
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=119
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=426
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=213
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=107
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=299
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=150
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=75
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=38
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=314
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=157
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=353
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=317
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=159
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=264
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=132
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=271
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=136
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=68
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=341
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=171
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=86
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=43
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=343
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=172
      warnings.warn(


    10243
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=321
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=161
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=81
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=265
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=439
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=220
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=110
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=486
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=243
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=122
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=61
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=326
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=163
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=82
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=442
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=221
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=111
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=272
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=289
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=145
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=73
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=315
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=367
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=405
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=203
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=306
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=153
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=269
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=91
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=46
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=93
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=47
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=328
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=164
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=288
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=298
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=352
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=176
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=88
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=379
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=190
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=95
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=48
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=462
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=231
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=116
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=58
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=313
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=267
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=134
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=273
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=137
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=475
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=238
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=44
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=488
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=244
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=296
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=148
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=310
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=155
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=503
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=252
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=126
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=399
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=200
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=458
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=229
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=115
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=441
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=149
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=357
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=179
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=60
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=293
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=380
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=308
      warnings.warn(


    50587
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=396
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=411
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=206
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=103
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=52
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=358
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=90
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=45
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=347
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=302
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=151
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=428
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=214
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=276
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=511
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=256
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=128
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=64
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=32
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=382
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=191
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=96
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=327
      warnings.warn(


    60161
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=471
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=489
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=245
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=123
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=401
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=364
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=182
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=369
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=41
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=457
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=29
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=355
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=178
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=89
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=433
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=217
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=418
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=209
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=53
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=27
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=334
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=167
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=387
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=194
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=97
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=49
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=436
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=409
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=205
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=427
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=509
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=255
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=285
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=143
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=198
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=99
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=50
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=463
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=232
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=402
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=201
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=101
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=51
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=424
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=212
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=106
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=350
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=423
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=383
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=192
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=333
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=26
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=339
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=170
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=85
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=490
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=62
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=31
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=363
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=371
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=186
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=450
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=225
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=113
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=57
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=505
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=253
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=127
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=94
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=24
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=429
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=319
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=473
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=281
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=497
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=249
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=125
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=63
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=291
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=30
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=501
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=251
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=481
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=241
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=121
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=268
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=397
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=199
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=100
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=25
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=499
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=250
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=403
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=202
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=461
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=495
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=248
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=496
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=309
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=295
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=286
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=283
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=300
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=284
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=336
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=260
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=254
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=438
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=413
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=207
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=479
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=240
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=498
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=432
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=216
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=470
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=235
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=467
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=234
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=425
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=453
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=227
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=344
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=377
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=189
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=362
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=417
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=345
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=173
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=278
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=139
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=449
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=431
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=395
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=445
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=223
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=117
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=59
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=421
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=211
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=507
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=354
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=177
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=375
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=188
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=446
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=337
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=169
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=360
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=180
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=388
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=366
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=183
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=338
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=378
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=394
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=197
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=385
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=193
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=342
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=263
      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=469
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=236
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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=483
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=242
      warnings.warn(


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      warnings.warn(


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      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=270
      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=346
      warnings.warn(


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      warnings.warn(
    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=166
      warnings.warn(


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      warnings.warn(


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    /home/thomasaqa/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:222: UserWarning: n_fft=512 is too small for input signal of length=257
      warnings.warn(


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      warnings.warn(


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```python
#%% Q-0.2.2 - Plot the various transforms 

# Just a little helper to make your figures pretty
from helper_plot import hdr_plot_style, plot_data
hdr_plot_style()

######################
plot_data(data_struct["spectrum_power"][0])

######################

```

### Features

<div markdown = "1">

As you might have noted from the previous exercice, most spectral transforms have a very high dimensionality, and might not be suited to exhibit the relevant structure of different classes. To that end, we provide a set of functions for computing several spectral features in the `helper_data` folder, we redirect interested readers to this [exhaustive article](http://recherche.ircam.fr/anasyn/peeters/ARTICLES/Peeters_2003_cuidadoaudiofeatures.pdf) on spectral features computation.

  |**File**|*Transform*|
  |-------:|:----------|
  |`spectral_centroid`|Spectral centroid|
  |`spectral_bandwidth`|Spectral bandwidth|
  |`spectral_contrast`|Spectral contrast|
  |`spectral_flatness`|Spectral flatness|
  |`spectral_rolloff`|Spectral rolloff|

Once again, we provide a function to perform the computation of different features on a complete set. Note that for each feature, we compute the temporal evolution in a vector along with the mean and standard deviation of each feature. We only detail the resulting data structure for a single feature (`SpectralCentroid`).  

``` Python
def data_struct = computeFeatures(data_struct)
     """ data_struct   : Dataset structure with filenames """
    return data_struct

% Returns the data_struct structure with
data_struct["spectral_centroid"]      # Temporal value of a feature
data_struct["spectral_centroid_mean"] # Mean value of that feature
data_struct["spectral_centroid_std"]  # Standard deviation
```

***

**Exercise**

  1. Launch the feature computation procedure and check the corresponding structure
  2. This time for each class, superimpose the plots of various features on a single plot, along with a boxplot of mean and standard deviations. You should obtain plots similar to those shown afterwards.
  3. What conclusions can you make on the discriminative power of each feature ?
  4. Perform scatter plots of the mean features for all the dataset, while coloring different classes.
  5. What conclusions can you make on the discriminative power of mean features ?

***


```python
#%%
# 0.3 - Compute a set of temporal and spectral features
# (may take around 1-2 minutes)
from helper_data import compute_features
data_struct = compute_features(data_struct);
```

        - Performing features.



```python
#%% Q-0.3.2 - Plot the various features 

# Just a little helper to make your figures pretty
from helper_plot import hdr_plot_style
hdr_plot_style()
# Use these styles for boxplot
boxprops=dict(linewidth=3, color='white')
whiskerprops=dict(linewidth=3, color='white')
medianprops=dict(linewidth=2.5, color='firebrick')
flierprops = dict(markeredgecolor='white', markerfacecolor='firebrick')

######################
fig1=plt.figure(figsize=(24,12))
#labels = ["spectral_centroid_mean","spectral_bandwidth_mean","spectral_rolloff_mean","loudness_mean"]
labels= ["spectral_contrast_mean"]

for i in range(16):    
    ax=fig1.add_subplot(2,8,i+1)
    to_plot=np.zeros([len(labels),np.sum(data_struct["classes"]==i)])
    for j in range(len(labels)):
        to_plot[j,:]=np.array(data_struct[labels[j]])[data_struct["classes"]==i]
    ax.boxplot(to_plot.T,medianprops=medianprops,boxprops=boxprops,whiskerprops=whiskerprops,flierprops=flierprops)
######################

```


```python
data_struct.keys()
```




    dict_keys(['filenames', 'classes', 'class_names', 'signal', 'srate', 'spectrum_power', 'spectrum_mel', 'spectrum_chroma', 'spectrum_CQT', 'features_spectral', 'loudness', 'loudness_mean', 'loudness_std', 'spectral_centroid', 'spectral_centroid_mean', 'spectral_centroid_std', 'spectral_bandwidth', 'spectral_bandwidth_mean', 'spectral_bandwidth_std', 'spectral_contrast', 'spectral_contrast_mean', 'spectral_contrast_std', 'spectral_flatness', 'spectral_flatness_mean', 'spectral_flatness_std', 'spectral_rolloff', 'spectral_rolloff_mean', 'spectral_rolloff_std'])




```python
#%% Q-0.3.4 - Observe the distribution of classes for different features
from helper_plot import hdr_plot_style
# This allows to use 3D rendering in matplotlib
from mpl_toolkits.mplot3d import Axes3D

# Create a vector of random colors for each class
colorVect = np.zeros((3, len(data_struct["class_names"])));
for c in range(len(data_struct["class_names"])):
    colorVect[:,c] = np.random.rand(3);
```


```python

######################
fig=plt.figure(figsize=(12,8))

ax = fig.add_subplot(111, projection = '3d')
for i in range(len(data_struct["class_names"])):
    x=np.array(data_struct["spectral_contrast_mean"])[data_struct["classes"]==i]
    y=np.array(data_struct["loudness_mean"])[data_struct["classes"]==i]
    z=np.array(data_struct["spectral_bandwidth_mean"])[data_struct["classes"]==i]
    ax.scatter(y,z,x,s=30,c=colorVect[:,i].reshape(1,-1))
######################
```


```python
data_struct.keys()
```




    dict_keys(['filenames', 'classes', 'class_names', 'signal', 'srate', 'spectrum_power', 'spectrum_mel', 'spectrum_chroma', 'spectrum_CQT', 'features_spectral', 'loudness', 'loudness_mean', 'loudness_std', 'spectral_centroid', 'spectral_centroid_mean', 'spectral_centroid_std', 'spectral_bandwidth', 'spectral_bandwidth_mean', 'spectral_bandwidth_std', 'spectral_contrast', 'spectral_contrast_mean', 'spectral_contrast_std', 'spectral_flatness', 'spectral_flatness_mean', 'spectral_flatness_std', 'spectral_rolloff', 'spectral_rolloff_mean', 'spectral_rolloff_std'])



That's it for this tutorial, now remember that we can use any form of description (features) as a basis for learning algorithms. We will see in the next tutorial what we an do with these features.

1846c5fcb9d0549296096f96fff57c52c9d71f3b
ipynb
Jupyter Notebook
01a_machine_learning.ipynb
RisseThomas/atiam_ml
28a963f9a7504b1b9600d438a35c4ca4a737605d
MIT
01a_machine_learning.ipynb
RisseThomas/atiam_ml
28a963f9a7504b1b9600d438a35c4ca4a737605d
MIT
01a_machine_learning.ipynb
RisseThomas/atiam_ml
28a963f9a7504b1b9600d438a35c4ca4a737605d
MIT
Qwen/Qwen-72B
1. YES
2. YES