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asteroid

The PyTorch-based audio source separation toolkit for researchers

atst-sed

This repo includes the official implementations of "Fine-tune the pretrained ATST model for sound event detection".

beam-guided-tasnet

Beam-guided TasNet

beamforming-for-speech-enhancement

simple delaysum, MVDR and CGMM-MVDR

c8dasr-baseline-nemo

NeMo: a toolkit for conversational AI

deepship

faceswap

Deepfakes Software For All

fast-rir

This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.

ir-gan

Augmenting Room Impulse Response

jetson-containers

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

nbss

The official repo of NBC & SpatialNet

nn-gev

Neural network supported GEV beamformer

odas

ODAS: Open embeddeD Audition System

openvoice

Instant voice cloning by MyShell.

pygsound

Impulse response generation based on state-of-the-art geometric sound propagation engine.

slidev

Presentation Slides for Developers

speechbrain

A PyTorch-based Speech Toolkit

srp-dnn

A python implementation of “SRP-DNN: Learning Direct-Path Phase Difference for Multiple Moving Sound Source Localization” [ICASSP 2022]

sssfastmnmf

The code for multi-channel source separation and dereverberation such as FastMNMF1, FastMNMF2, and AR-FastMNMF2.

stable-diffusion-webui

Stable Diffusion web UI

stablevideo

[ICCV 2023] StableVideo: Text-driven Consistency-aware Diffusion Video Editing

sudo_rm_rf

Code for SuDoRm-Rf networks for efficient audio source separation. SuDoRm-Rf stands for SUccessive DOwnsampling and Resampling of Multi-Resolution Features which enables a more efficient way of separating sources from mixtures.

tac

transform-average-concatenate (TAC) method for end-to-end microphone permutation and number invariant ad-hoc beamforming.

tts_coqui

🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

vits-pytorch

本项目是基于Pytorch的语音合成项目，使用的是VITS，VITS是一种语音合成方法，这种时端到端的模型使用起来非常简单，不需要文本对齐等太复杂的流程，直接一键训练和生成，大大降低了学习门槛。

voiceprintrecognition-pytorch

本项目使用了EcapaTdnn模型实现的声纹识别