28 Open source projects that are alternatives of or similar to Voice-Separation-and-Enhancement

A curated list of awesome Speech Enhancement papers, libraries, datasets, and other resources.

Deep learning based Speech Beamforming

End-to-End Speech Processing Toolkit

Split multi-channel WAV files into single channel WAV files.

(NOT Official) Implementation DC-UNet (ICLR 2019)

💎 A list of accessible speech corpora for ASR, TTS, and other Speech Technologies

A speech dereverberation algorithm, also called wpe

Pytorch implements Deep Clustering: Discriminative Embeddings For Segmentation And Separation

speech enhancement GAN on waveform/log-power-spectrum data using Improved WGAN

A statistical model-based Speech Enhancement Using MMSE-STSA

Real time monaural source separation base on fully convolutional neural network operates on Time-frequency domain.

Neural Turing machine for source separation in Tensorflow

The official repo of "Multi-channel Narrow-band Deep Speech Separation with Full-band Permutation Invariant Training", "Multichannel Speech Separation with Narrow-band Conformer" and "NBC2: Multichannel Speech Separation with Revised Narrow-band Conformer".

In this work we propose two postprocessing approaches applying convolutional neural networks (CNNs) either in the time domain or the cepstral domain to enhance the coded speech without any modification of the codecs. The time domain approach follows an end-to-end fashion, while the cepstral domain approach uses analysis-synthesis with cepstral d…

Pytorch implementation of subband decomposition

Script to calculate SNR and SDR using python

🌲 春松客服，智能客服系统，开源客服系统 ，机器人客服，客服系统开发框架，多渠道

A flexible data historian based on InfluxDB, Grafana, MQTT and more. Free, open, simple.

A unofficial Pytorch implementation of Google's VoiceFilter

Constrained Permutation Invariant Training, Speech Separation

According to funcwj's uPIT, the training code supporting multi-gpu is written, and the Dataloader is reconstructed.

A PyTorch implementation of Time-domain Audio Separation Network (TasNet) with Permutation Invariant Training (PIT) for speech separation.

UniSpeech - Large Scale Self-Supervised Learning for Speech

Source code for the paper titled "Speech Denoising without Clean Training Data: a Noise2Noise Approach". Paper accepted at the INTERSPEECH 2021 conference. This paper tackles the problem of the heavy dependence of clean speech data required by deep learning based audio denoising methods by showing that it is possible to train deep speech denoisi…

A Conditional Generative Adverserial Network (cGAN) was adapted for the task of source de-noising of noisy voice auditory images. The base architecture is adapted from Pix2Pix.

No description or website provided.

This is the repo of the manuscript "Embedding and Beamforming: All-Neural Causal Beamformer for Multichannel Speech Enhancement", which was submitted to ICASSP2022.

Speech Enhancement Metrics (PESQ, CSIG, CBAK, COVL)