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myminesweep

一款Android扫雷游戏

p.808

This is an open-source implementation of the ITU P.808 standard for "Subjective evaluation of speech quality with a crowdsourcing approach" (see https://www.itu.int/rec/T-REC-P.808/en). It uses Amazon Mechanical Turk as the crowdsourcing platform. It includes implementations for Absolute Category Rating (ACR), Degradation Category Rating (DCR), and Comparison Category Rating (CCR).

pyaec

simple and efficient python implemention of a series of adaptive filters. including time domain adaptive filters(lms、nlms、rls、ap、kalman)、nonlinear adaptive filters(volterra filter、functional link adaptive filters)、frequency domain adaptive filters(frequency domain adaptive filter、frequency domain kalman filter) for acoustic echo cancellation.

rnnoise

Recurrent neural network for audio noise reduction

segan_pytorch

Speech Enhancement Generative Adversarial Network in PyTorch

seq2seq

Sequence to Sequence Learning with Keras

speech-separation-paper-tutorial

A must-read paper for speech separation based on neural networks

speech-transformer

A PyTorch implementation of Speech Transformer, an End-to-End ASR with Transformer network on Mandarin Chinese.

speechdenoisingdnn

Removing various types of noises present in the speech using Deep Neural Networks

spkai

spleeter

Deezer source separation library including pretrained models.

ultra-light-fast-generic-face-detector-1mb

💎1MB lightweight face detection model (1MB轻量级人脸检测模型)

wav2letter

Facebook AI Research Automatic Speech Recognition Toolkit

wave-u-net-for-speech-enhancement

Implement [Wave-U-Net](https://arxiv.org/abs/1806.03185) by PyTorch, and migrate it to the speech enhancement area.