speaker-recognition

NeMo: a toolkit for conversational AI

A PyTorch-based Speech Toolkit

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.

SincNet is a neural architecture for efficiently processing raw audio samples.

an open-source implementation of sequence-to-sequence based speech processing engine

In defence of metric learning for speaker recognition

🔈 Deep Learning & 3D Convolutional Neural Networks for Speaker Verification

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

speaker diarization by uis-rnn and speaker embedding by vgg-speaker-recognition

The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.

Unofficial reimplementation of ECAPA-TDNN for speaker recognition (EER=0.86 for Vox1_O when train only in Vox2)

本项目使用了EcapaTdnn模型实现的声纹识别

Deep speaker embeddings in PyTorch, including x-vectors. Code used in this work: https://arxiv.org/abs/2007.16196

Research and Production Oriented Speaker Recognition Toolkit

Base on MFCC and GMM(基于MFCC和高斯混合模型的语音识别)

Keras implementation of ‘’Deep Speaker: an End-to-End Neural Speaker Embedding System‘’ (speaker recognition)

使用Tensorflow实现声纹识别

This repository contains audio samples and supplementary materials accompanying publications by the "Speaker, Voice and Language" team at Google.

[InterSpeech 2020] "AutoSpeech: Neural Architecture Search for Speaker Recognition" by Shaojin Ding*, Tianlong Chen*, Xinyu Gong, Weiwei Zha, Zhangyang Wang