dataset
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				|  | @ -0,0 +1,38 @@ | |||
| 
 | ||||
| from genericpath import isdir | ||||
| import librosa | ||||
| import os | ||||
| from torch.utils.data import IterableDataset | ||||
| import torch | ||||
| 
 | ||||
| 
 | ||||
| class Vctk(IterableDataset): | ||||
|     """Dataset object for Voice Bank Corpus (VCTK) Dataset""" | ||||
| 
 | ||||
|     def __init__(self,clean_path,noisy_path,sample_length=1,num_samples=None): | ||||
|          | ||||
|         if not os.path.isdir(clean_path): | ||||
|             raise ValueError(f"{clean_path} is not a valid directory") | ||||
| 
 | ||||
|         if not os.path.isdir(noisy_path): | ||||
|             raise ValueError(f"{clean_path} is not a valid directory") | ||||
| 
 | ||||
|         self.clean_path = clean_path | ||||
|         self.noisy_path = noisy_path | ||||
| 
 | ||||
|         if num_samples is None: | ||||
|             self.num_samples = len([file for file in os.listdir(clean_path) if file.endswith(".wav")]) | ||||
|         else: | ||||
|             self.num_samples = num_samples | ||||
| 
 | ||||
|         self.sample_length = max(0.1,sample_length) | ||||
| 
 | ||||
|     def __iter__(self): | ||||
| 
 | ||||
|          | ||||
| 
 | ||||
| 
 | ||||
|         pass | ||||
| 
 | ||||
|     def __len__(self): | ||||
|         pass | ||||
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