Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
SincNet is a neural architecture for efficiently processing raw audio samples.
Frontier CoreML audio models in your apps — text-to-speech, speech-to-text, voice activity detection, and speaker diarization. In Swift, powered by SOTA open source.
PyTorch implementation of "Generalized End-to-End Loss for Speaker Verification" by Wan, Li et al.
This repository contains audio samples and supplementary materials accompanying publications by the "Speaker, Voice and Language" team at Google.
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.
Speaker Identification System (upto 100% accuracy); built using Python 2.7 and python_speech_features library
Simple d-vector based Speaker Recognition (verification and identification) using Pytorch
Deep Learning - one shot learning for speaker recognition using Filter Banks
Identifying people from small audio fragments
Official Implementation of the work "Audio Mamba: Bidirectional State Space Model for Audio Representation Learning"
A light weight neural speaker embeddings extraction based on Kaldi and PyTorch.
打造最简单的TTS前端集合,最简单的有声小说制作工作流。基于正则规则对小说进行分句,基于RoBERTa对小说中的对话进行说话人识别,从而实现一键式生成多人有声小说。多说话人的语音合成,高质量的有声小说制作。
[SLT'24] The official implementation of SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model
This repo contains my attempt to create a Speaker Recognition and Verification system using SideKit-1.3.1
A data annotation pipeline to generate high-quality, large-scale speech datasets with machine pre-labeling and fully manual auditing.
Source code for paper "Who is real Bob? Adversarial Attacks on Speaker Recognition Systems" (IEEE S&P 2021)
Pytorch implementation of "Generalized End-to-End Loss for Speaker Verification"
Pytorch implementation of Generalized End-to-End Loss for speaker verification
A tool for summarizing dialogues from videos or audio
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