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Combine sound source separation with SRP-PHAT to achieve multi-source localization.
Neural Network based Sound Source Localization Models
speech enhancement\speech seperation\sound source localization
Multi-Scale Temporal Frequency Convolutional Network With Axial Attention for Speech Enhancement
Speech enhancement in noisy and reverberant environments using deep neural networks
An AI-Powered Speech Processing Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Enhancement, Separation, and Target Speaker Extraction, etc.
This repository contains the audio samples for "D2Former: A Fully Complex Dual-Path Dual-Decoder Conformer Network using Joint Complex Masking and Complex Spectral Mapping for Monaural Speech Enhan…
Explicit Estimation of Magnitude and Phase Spectra in Parallel for High-Quality Speech Enhancement
speaker diarization by uis-rnn and speaker embedding by vgg-speaker-recognition
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
Research and Production Oriented Speaker Verification, Recognition and Diarization Toolkit
Robust Speech Recognition via Large-Scale Weak Supervision
The official PyTorch implementation of "FullSubNet+: Channel Attention FullSubNet with Complex Spectrograms for Speech Enhancement".
DCCRN: Deep Complex Convolution Recurrent Network
The PyTorch-based audio source separation toolkit for researchers
Uformer: A Unet based dilated complex & real dual-path conformer network for simultaneous speech enhancement and dereverberation
Implementation of paper "DPCRN: Dual-Path Convolution Recurrent Network for Single Channel Speech Enhancement"
Offline CGMM and CGMM with spatial prior distribution in an online manner
speech-enhacement
Implementation of the CGMM-MVDR beamforming (for python version please refer to https://github.com/funcwj/setk)
Noise supression using deep filtering