Speech-to-text / ASR with word-level timestamps and diarization
WhisperX is a Python library that performs fast automatic speech recognition with word-level timestamps and speaker diarization, using faster-whisper for batched inference and pyannote for diarization.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
choose when you want a single library that also provides speaker recognition in addition to transcription and diarization
Speechlib is a library that unifies speaker diarization, transcription and speaker recognition in a single pipeline to create transcripts for audio conversations with actual speaker names and time tags. This library also contains audio preprocessor functions.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
script/notebook-based Whisper+pyannote diarization pipeline, less maintainable as a dependency
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
choose for word-level timestamps only without diarization; AGPL-licensed, active
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
choose for a Rust-native streaming ASR with diarization using NVIDIA Parakeet
very fast speech-to-text, diarization, streaming (even in CPU) with NVIDIA Parakeet in Rust
choose for real-time streaming ASR with diarization and OpenAI/Deepgram-compatible APIs
Real-time, local speech-to-text with streaming ASR, speaker diarization, translation, and OpenAI/Deepgram-compatible APIs.
simple script combining pyannote and Whisper for ASR+diarization, not a packaged library
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
older optimized Whisper pipeline with multiple inference engines, unmaintained since 2 years
An Optimized Speech-to-Text Pipeline for the Whisper Model Supporting Multiple Inference Engine
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
web service wrapper around Whisper, lacks word-level timestamps and diarization
OpenAI Whisper ASR Webservice API
command-line client for Whisper compatible with OpenAI's original CLI, no diarization
Whisper command line client compatible with original OpenAI client based on CTranslate2.
live transcription GUI for internal speaker output and microphone input
Ecoute is a live transcription tool that provides real-time transcripts for both the user's microphone input (You) and the user's speakers output (Speaker) in a textbox.
standalone Windows executables for Whisper, no diarization features
Whisper & Faster-Whisper standalone executables for those who don't want to bother with Python.
subtitle generation tool with Web-UI/CLI, higher-level than a library
🎞️ Subtitles generation tool (Web-UI + CLI + Python package) powered by OpenAI's Whisper and its variants 🎞️
web API for Whisper transcription, no word timestamps or diarization
This project provides an API with user level access support to transcribe speech to text using a finetuned and processed Whisper ASR model.
turnkey self-hosted transcription/diarization service with LLM summarization
turnkey self-hosted offline transcription and diarization service with llm summary
one-command CLI to extract text from videos/audio, no developer API
Snap any video URL or audio file into plaintext. No GPU. No cloud. One command.
near-real-time WebSocket transcription service, not a batch library
Near-Realtime audio transcription using self-hosted Whisper and WebSocket in Python/JS
These projects were analysed and named whisperX among their alternatives. The relationship is not symmetric — how whisperX rates them is a separate judgement, made when whisperX is analysed in its own right.
calls whisperX “Whisper library/CLI with word-level timestamps and diarization; choose for accurate alignment.”
Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.
calls whisperX “Choose it when word-level timestamps and speaker diarization matter more than the seed's pure throughput optimization.”
calls whisperX “choose for Whisper-based ASR with word-level timestamps and diarization.”
Speech recognition module for Python, supporting several engines and APIs, online and offline.
calls whisperX “Choose over Vibe when you need word-level timestamps and diarization inside your own Python pipeline.”
Transcribe on your own!
calls whisperX “choose for accurate word-level timestamps and diarization on top of Whisper in Python.”
Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.
calls whisperX “when you need fast offline word-level timestamps and diarization from Whisper; no streaming”
Real-time, local speech-to-text with streaming ASR, speaker diarization, translation, and OpenAI/Deepgram-compatible APIs.
calls whisperX “choose for word-level timestamps and diarization on Whisper, not a general speech framework.”
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)