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---
title: Mandarin Tone Evaluation
emoji: 📉
colorFrom: gray
colorTo: blue
sdk: gradio
sdk_version: 4.7.1
app_file: app.py
pinned: false
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
# Team 3 Project - Tone Evaluation
## Overview
Welcome to Team 3's Tone Evaluation project! This repository contains the necessary files and resources for our project, which focuses on data processing, training, testing, and a user interface (UI) demo.
## Project Structure
- **Data Processing File**: [dataset.py](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/dataset.py)
- This script is responsible for processing the raw data and preparing it for training and testing.
- It takes input audio in wav format, and transfer audio into mel spectrum form and fundamental frequency form. These will be the two main features for the model to analyze.
- We convert the pinyin and tone into numerical lables by providing a text file and link each pinyin to a index.
- **Train File**: [train.py](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/train.py)
- This file contains the code for training our tone evaluation model. We use CNN+CTC model for this task.
- **Test File**: [test.py](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/test.py)
- Use this script to evaluate the performance of our trained model on test data.
- Currenty, we set the model to only accepct wav format audio, and after loading the audio, model will predict the tone sequence for the sentence.
- **UI Demo**: [ui_space](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation)
- Explore the user interface demo to interact with the tone evaluation model.
- You can upload wav format audio to our UI and see the evaluation result. We also provided some audio files for you to directly use.
## Dataset
We provide two versions of the dataset:
- **Full Size Version**: Download from Kaggle [full_dataset](https://huggingface.co/datasets/CS5647Team3/full_dataset)
- **Small Size Zip Version**: Zip file, Download from [data_mini](https://huggingface.co/datasets/CS5647Team3/data_mini)
Additionally, we offer a text file for Pinyin encoding: [pinyin.txt](https://huggingface.co/spaces/CS5647Team3/Mandarin_Tone_Evaluation/blob/main/pinyin.txt). This file is crucial for understanding the encoding used in our dataset.
## Getting Started
Follow these steps to get started with our project:
1. Clone this repository to your local machine.
2. Run the data processing script: `python data_processing.py`
3. Train the model using: `python train.py`
4. Evaluate the model with: `python test.py`
5. Explore the UI demo: `python ui_demo.py`
## Additional Information
- If you encounter any issues or have questions, feel free to reach out to our team through emails.
- Dataset and preprocessing
- Shen Siyan shen[email protected]
- Ouyang Yanjia [email protected]
- Model Training
- Zhao Zhengkai
- [email protected]
- Liu Mingxuan
- [email protected]
We hope you find our project useful and insightful! Happy coding!
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