Cutting edge AI technology for automated audio transcription. A nice GUI for OpenAIs Whisper and pyannote (speaker identification)

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Cog implementation of transcribing + diarization pipeline with Whisper & Pyannote

Parakeet 0.6b V2 + Pyannote diarization behind a Whisper API

Tool for automatic transcription and speaker diarization based on whisper and pyannote.

Whisper from OpenAi and diarization with Pyannote

Transcription and diarization (speaker identification)

Fuse whisper and pyannote results

AI-powered local meeting transcription with automatic speaker identification using whisper.cpp, pyannote.audio, and LLM-based name matching

A Python package to transcribe speech by Whisper with diarization (speaker identification) using pyannote.audio and send the results to OpenAI Chat API to generate, for example, the summary of the conversation.

Generate transcriptions and subtitles using OpenAI whisper as a base model, stable-ts/whisperx as a timestamp stabilizer using ASR models and pyannote/nemo models in order to identify different speakers.

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Whisperize - A Python application for real-time audio transcription and speaker diarization using Faster-Whisper and PyAnnote.

speech to text gui for different (mostly Whisper, also Voxtral) models and backends, including whisper.cpp, mlx-whisper, faster-whisper, ctranslate2; applies pyannote for diarization

Speaker Diarization with Pyannote and Whisper.cpp

Google Colab notebook which will take in an audio file, transcribe it using OpenAI Whisper, identify all speakers using pyannote.audio, and make the full marked up transcript available for passing into an LLM for querying.

A powerful, fully-local audio transcription and speaker diarization tool using Whisper and pyannote.audio

🎵 Complete offline audio transcription system with speaker diarization using OpenAI Whisper and PyAnnote. Features automatic audio cleaning, precise timestamps, multiple output formats (JSON/TXT/Markdown), and support for 20+ audio formats. No external APIs required - works entirely offline.

Automatic Speech Recognition + Speaker Diarization using PyAnnote and OpenAI Whisper.

Use PyAnnote and Whisper to transcribe F1 team radio

Transcription and diarization using Whisper and Pyannote with NodeJS

Verbatim Swedish Whisper transcription and speaker diarization with word-level time stamps (using kb-whisper and pyannote)

End-to-end Speaker Diarization and Transcription system combining Faster-Whisper (ASR), Pyannote (VAD/segmentation), NVIDIA NeMo (speaker embeddings + clustering), and CTC forced aligner for precise word-level timestamps. Includes a React + Vite frontend and Flask + FastAPI backend for easy audio upload, diarized transcripts, and summaries.

Subtitle generation w/ Speaker Diarization using Whisper and pyannote.audio

Audio transcription based in pyannote and whisper

Speech audio (i.e., interview) transcription with Whisper AI and speaker diarization with pyannote.

Python speaker diarization with OpenAI Whisper ASR & pyannote.audio for accurate multi‑speaker transcription & labeling.

Simple interface to upload, transcribe, diarize, and create subtitles using whisper-large-v3, pyannote/segmentation 3.0 and pyannote/speaker-diarization-3.1 (CLI in development)

ten vad + pyannote embedding + whisper 实现说话人识别 + 语音识别

CLI for automating the creation of subtitles using whisper and pyannote. Accepts batch or single audio and video files.