speaker-diarization

A PyTorch-based Speech Toolkit

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

A curated list of awesome Speaker Diarization papers, libraries, datasets, and other resources.

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

Python re-implementation of the (constrained) spectral clustering algorithms in "Speaker Diarization with LSTM" and "Turn-to-Diarize" papers.

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

End-to-End Neural Diarization

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

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

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

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

Discriminative Neural Clustering for Speaker Diarisation

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

A data annotation pipeline to generate high-quality, large-scale speech datasets with machine pre-labeling and fully manual auditing.

Pytorch implementation of Generalized End-to-End Loss for speaker verification

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

PyTorch implementation of Densely Connected Time Delay Neural Network

speaker diarization system using an LSTM

A lightweight library to compute Diarization Error Rate (DER).

Scripts for LIUM SpkDiarization tools

🔭 Speaker diarization via transfer learning

Neural network based similarity scoring for diarization (pytorch implementation of "LSTM based Similarity Measurement with Spectral Clustering for Speaker Diarization")

speaker diarization system using an LSTM

neural network based speaker embedder

Code for our ACML and INTERSPEECH papers: "Speaker Diarization as a Fully Online Bandit Learning Problem in MiniVox".

Speaker Diarization is the first step in many early audio processing and aims to solve the problem ”who spoke when”. It therefore relies on efficient use of temporal information from extracted audio features.

Simplified diarization pipeline using some pretrained models - audio file to diarized segments in a few lines of code

VB Diarization with Eigenvoice and HMM Priors, refactored