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

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

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

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

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

The S3PRL speech toolkit: self-supervised pre-training and representation learning of Mockingjay, TERA, A-ALBERT, APC, and more to come. With easy-to-use standard downstream evaluation scripts including phone classification, speaker recognition, and ASR. (All in Pytorch!)

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

In defence of metric learning for speaker recognition

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

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

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.

An Android ChatBot powered by Watson Services - Assistant, Speech-to-Text and Text-to-Speech on IBM Cloud.

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

Identifying people from small audio fragments

Speaker Identification System (upto 100% accuracy); built using Python 2.7 and python_speech_features library

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

This repository contains audio samples and supplementary materials accompanying publications related to the speaker-id team at Google.

Time delay neural network (TDNN) implementation in Pytorch using unfold method

Share some recent speaker recognition papers and their implementations.

Simple d-vector based Speaker Recognition (verification and identification) using Pytorch

PyTorch implementation of the Factorized TDNN (TDNN-F) from "Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks" and Kaldi

A program for automatic speaker identification using deep learning techniques.

Speaker identification with VGGVox network

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

A light weight neural speaker embeddings extraction based on Kaldi and PyTorch.

基于Flask Web的中文自动语音识别演示系统,包含语音识别、语音合成、声纹识别之说话人识别。

An Android ChatBot powered by IBM Watson Services (Assistant V1, Text-to-Speech, and Speech-to-Text with Speaker Recognition) on IBM Cloud.

This repo contains my attempt to create a Speaker Recognition and Verification system using SideKit-1.3.1

It is a complete project of voiceprint recognition or speaker recognition.

Speaker recognition library based on MARF for raspberry pi and other SBCs.