speaker-identification

Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

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.

very fast speech-to-text, diarization, streaming (even in CPU) with NVIDIA Parakeet in Rust

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.

Multi-speaker separation, identification, diarization ALL-IN-ONE. It can isolate the target speaker from a conversation audio and do ASR.

Local-first meeting transcription — audio & transcripts never leave your machine. Live captions + upload diarization + voice matching.

Speakerbox: Fine-tune Audio Transformers for speaker identification.

Speaker identification powered by pyannote and resemblyzer

Awesome Speech Dataset, including download links and a brief explanation for each resource. These datasets provide diverse and high-quality speech data covering various domains such as conversational, academic, political, and more.

This repository contains a short introduction on the topic of audio and speech processing -- from basics to applications.