Choose when you need word-level timestamps and speaker diarization in a Python pipeline rather than in-browser inference.
WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
- 23.7k
- Python
- BSD-2-Clause
browser speech recognition / in-browser ASR
A browser-based web app that runs Whisper speech recognition locally using Transformers.js.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose when you need word-level timestamps and speaker diarization in a Python pipeline rather than in-browser inference.
WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
Choose when you need a Python/notebook pipeline that adds speaker diarization to Whisper transcriptions.
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
Choose when you need a self-hosted near-live transcription server rather than client-side browser inference.
A nearly-live implementation of OpenAI's Whisper.
Choose when you need a self-hosted OpenAI-compatible speech API for server-side transcription.
Choose when you need a queued Whisper transcription service with HTTP API and GUI.
Whisper as a Service (GUI and API with queuing for OpenAI Whisper)
Choose when you need a Python package/CLI to generate subtitles from media files.
🎞️ Subtitles generation tool (Web-UI + CLI + Python package) powered by OpenAI's Whisper and its variants 🎞️
Choose when you need faster CPU/GPU Whisper inference via a command-line client using CTranslate2.
Whisper command line client compatible with original OpenAI client based on CTranslate2.
Choose when you need low-latency streaming transcription of audio in a Python framework.
Whisper-Flow is a framework designed to enable real-time transcription of audio content using OpenAI’s Whisper model. Rather than processing entire files after upload (“batch mode”), Whisper-Flow accepts a continuous stream of audio chunks and produces incremental transcripts immediately.
Choose when you need a multi-user HTTP API around a fine-tuned Whisper model.
This project provides an API with user level access support to transcribe speech to text using a finetuned and processed Whisper ASR model.
Choose when you need a self-hosted Docker ASR API endpoint for speech-to-text.
OpenAI Whisper ASR Webservice API
Choose when you need real-time streaming transcription of long audio instead of browser batch inference.
Whisper realtime streaming for long speech-to-text transcription and translation
Choose when you need word-level timestamps and confidence scores from a Python ASR pipeline.
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
Choose when you need a production end-to-end ASR toolkit and are not tied to Whisper models.
Production First and Production Ready End-to-End Speech Recognition Toolkit
Choose when you need real-time local 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.
Choose when targeting Apple Silicon and you want native Swift on-device speech recognition.
On-device Speech AI for Apple Silicon
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Choose when you need a smaller, faster Whisper model for Python/server inference, but it is not a browser app and has no recent updates.
Distilled variant of Whisper for speech recognition. 6x faster, 50% smaller, within 1% word error rate.
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
Choose when you want an offline desktop GUI for transcription instead of a browser-based app.
Transcribe on your own!
Choose when you want a self-hosted web UI for transcribing and editing subtitles, not an embeddable browser ASR app.
Transcribe any audio to text, translate and edit subtitles 100% locally with a web UI. Powered by whisper models!
Choose when you want a local Gradio web UI for subtitle generation rather than browser-side Whisper execution.
A Web UI for easy subtitle using whisper model.
Choose when you want a PHP web app for file transcription and translation rather than an in-browser tool.
Transcribe and translate your audio files - for free
Choose when you want a desktop GUI for offline transcription and translation instead of a browser app.
Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.
Choose when you want a desktop app for subtitle generation, translation, dubbing, and burning rather than a browser ASR app.
视频转字幕、字幕翻译、AI 配音与声音克隆、字幕烧录——免费开源的一站式桌面工具。基于 Whisper / FunASR 等本地模型离线语音转文字,批量处理 + 全平台 GPU 加速,跨 Windows / macOS / Linux。Free, open-source desktop app to generate, translate, dub & burn video subtitles — local Whisper speech-to-text, AI dubbing & voice cloning, offline, GPU-accelerated.
These projects were analysed and named whisper-web among their alternatives. The relationship is not symmetric — how whisper-web rates them is a separate judgement, made when whisper-web is analysed in its own right.
calls whisper-web “browser-based Whisper transcription via Transformers.js; choose for zero-install client-side work, though stale and basic.”
Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.
calls whisper-web “Use over Vibe if you want a zero-install browser-only transcription demo, accepting an unmaintained and much narrower tool.”
Transcribe on your own!
calls whisper-web “Choose it when you need in-browser Whisper transcription with no backend/Python dependency.”