MustafaElkhateeb/ASR-Egypt

This is the repository of Voiceless Voice team for the AIC Competition 2 This is the repository of Voiceless Voice team for the AIC Competition 2 - Speech Preprocessing - Text Preprocessing - Working Techniques - Feature Extraction - Model Building and training ------------------------------------------------------ Audio Preprocessing - Remove noise from speech - Trim audio to remove silence ------------------------------------------------------- Remove non-Arabic Alphabet chars_to_ignore = ['>', ']', 'ل', 'ـ', ' ', 1: 'ر', 2: 'l', 3: 'ً', 4: 'ا', 5: 'ب', 6: 'م', 7: 'ك', 8: 'ق', 9: 'ز', 10: 'ص', 11: 'آ', 12: 'ئ', 13: 'غ', 14: 'ى', 15: 'ط', 16: 'ؤ', 17: 'ت', 18: 'ظ', 19: 'ج', 20: 'ذ', 21: 'ش', 22: 'إ', 23: 'خ', 24: 'ن', 25: 'ة', 26: ' ', 27: 'ي', 28: 'ه', 29: 'ء', 30: 'ح', 31: 'و', 32: 'ث', 33: 'ع', 34: 'أ', 35: 'س', 36: 'ف', 37: 'د', 38: 'ض', 39: ' '} ---------------------------------------------------------- Speech-Transformer Encoder( (lstm): LSTM(13, 128, batch_first=True, bidirectional=True) (pBLSTMs): Sequential( (0): pBLSTM( (blstm1): LSTM(512, 128, batch_first=True, bidirectional=True) (lock): LockedDropout() ) (1): pBLSTM( (blstm1): LSTM(512, 128, batch_first=True, bidirectional=True) (lock): LockedDropout() ) (2): pBLSTM( (blstm1): LSTM(512, 128, batch_first=True, bidirectional=True) (lock): LockedDropout() ) ) (key_network): Linear(in_features=256, out_features=128, bias=True) (value_network): Linear(in_features=256, out_features=128, bias=True) ) Bidirectional LSTM: The Bi-LSTM layer processes the input sequence in both forward and backward directions simultaneously. During the forward pass Teacher forcing: Teacher forcing acts like "training wheels." If the model makes a bad prediction, it is put back in place with the true value. Finally, we can make predictions using mixed teacher forcing.