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import librosa
import torch
import pandas as pd
from torch.utils.data import Dataset
class EmotionDataset(Dataset):
def __init__(self, csv_file, processor):
self.data = pd.read_csv(csv_file)
self.processor = processor
self.emotion_labels = {"joie": 0, "colère": 1, "neutre": 2}
def __len__(self):
return len(self.data)
def __getitem__(self, idx):
audio_path = self.data.iloc[idx, 0]
label = self.emotion_labels[self.data.iloc[idx, 1]]
waveform, _ = librosa.load(audio_path, sr=16000)
input_values = self.processor(waveform, return_tensors="pt", sampling_rate=16000).input_values
return input_values.squeeze(0), torch.tensor(label, dtype=torch.long)
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