A PyTorch-based Speech Toolkit
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Updated
Jun 18, 2024 - Python
A PyTorch-based Speech Toolkit
End-to-End Speech Processing Toolkit
The PyTorch-based audio source separation toolkit for researchers
Unofficial PyTorch implementation of Google AI's VoiceFilter system
A PyTorch implementation of Conv-TasNet described in "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" with Permutation Invariant Training (PIT).
PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."
UniSpeech - Large Scale Self-Supervised Learning for Speech
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation Pytorch's Implement
Tools for Speech Enhancement integrated with Kaldi
Real-time GCC-NMF Blind Speech Separation and Enhancement
A PyTorch implementation of DNN-based source separation.
A PyTorch implementation of "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" (see recipes in aps framework https://github.com/funcwj/aps)
Speech Enhancement based on DNN (Spectral-Mapping, TF-Masking), DNN-NMF, NMF
Deep neural network (DNN) for noise reduction, removal of background music, and speech separation
Executable code based on Google articles
A personal toolkit for single/multi-channel speech recognition & enhancement & separation.
Pytorch implements Deep Clustering: Discriminative Embeddings For Segmentation And Separation
deep clustering method for single-channel speech separation
A PyTorch implementation of Time-domain Audio Separation Network (TasNet) with Permutation Invariant Training (PIT) for speech separation.
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