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from pathlib import Path
import pandas as pd
from src.datasets.base_dataset import SimpleAudioFakeDataset
WAVEFAKE_SPLIT = {
"train": ['multi_band_melgan', 'melgan_large', 'parallel_wavegan', 'waveglow', 'full_band_melgan', 'melgan', 'hifiGAN'],
"test": ['multi_band_melgan', 'melgan_large', 'parallel_wavegan', 'waveglow', 'full_band_melgan', 'melgan', 'hifiGAN'],
"val": ['multi_band_melgan', 'melgan_large', 'parallel_wavegan', 'waveglow', 'full_band_melgan', 'melgan', 'hifiGAN'],
"partition_ratio": [0.7, 0.15],
"seed": 45
}
class WaveFakeDataset(SimpleAudioFakeDataset):
fake_data_path = "generated_audio"
jsut_real_data_path = "real_audio/jsut_ver1.1/basic5000/wav"
ljspeech_real_data_path = "real_audio/LJSpeech-1.1/wavs"
def __init__(self, path, subset="train", transform=None):
super().__init__(subset, transform)
self.path = Path(path)
self.fold_subset = subset
self.allowed_attacks = WAVEFAKE_SPLIT[subset]
self.partition_ratio = WAVEFAKE_SPLIT["partition_ratio"]
self.seed = WAVEFAKE_SPLIT["seed"]
self.samples = pd.concat([self.get_fake_samples(), self.get_real_samples()], ignore_index=True)
def get_fake_samples(self):
samples = {
"user_id": [],
"sample_name": [],
"attack_type": [],
"label": [],
"path": []
}
samples_list = list((self.path / self.fake_data_path).glob("*/*.wav"))
samples_list = self.filter_samples_by_attack(samples_list)
samples_list = self.split_samples(samples_list)
for sample in samples_list:
samples["user_id"].append(None)
samples["sample_name"].append("_".join(sample.stem.split("_")[:-1]))
samples["attack_type"].append(self.get_attack_from_path(sample))
samples["label"].append("spoof")
samples["path"].append(sample)
return pd.DataFrame(samples)
def filter_samples_by_attack(self, samples_list):
return [s for s in samples_list if self.get_attack_from_path(s) in self.allowed_attacks]
def get_real_samples(self):
samples = {
"user_id": [],
"sample_name": [],
"attack_type": [],
"label": [],
"path": []
}
samples_list = list((self.path / self.jsut_real_data_path).glob("*.wav"))
samples_list += list((self.path / self.ljspeech_real_data_path).glob("*.wav"))
samples_list = self.split_samples(samples_list)
for sample in samples_list:
samples["user_id"].append(None)
samples["sample_name"].append(sample.stem)
samples["attack_type"].append("-")
samples["label"].append("bonafide")
samples["path"].append(sample)
return pd.DataFrame(samples)
@staticmethod
def get_attack_from_path(path):
folder_name = path.parents[0].relative_to(path.parents[1])
return str(folder_name).split("_", maxsplit=1)[-1]
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