{"slug": "whisperx", "name": "WhisperX", "category": "ai", "category_name": "AI tools and apps", "description": "", "recommenders": 4, "commenters": 10, "warners": 1, "score": 3.596, "rising": -1.31, "first": "2025-11-18", "latest": "2026-07-07", "why": "I recommend WhisperX [2], it's the most complete CLI so far", "why_is_quote": true, "has_verdict": false, "sentiment": {"recommend": 5, "neutral": 4, "compare": 1, "warn": 1}, "spark": [1, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], "listed": true, "loved": [], "caveat": "", "short_quote": "I recommend WhisperX [2], it's the most complete CLI so far", "kind": "", "icon": false, "domain": null, "github_repo": "github.com/m-bain/whisperx", "official_url": "https://github.com/m-bain/whisperX", "pricing": "", "aliases": ["WhisperX", "whisperX"], "verdict": null, "praise": [{"label": "", "summary": "", "quotes": [{"id": 744940848, "item_id": 46558803, "url": "https://news.ycombinator.com/item?id=46558803", "by": "satvikpendem", "date": "2026-01-09", "version": null, "stance": "recommend", "quote": "I recommend WhisperX [2], it's the most complete CLI so far", "excerpt": "Batching is essentially running multiple instances at once, ie bundling 8 segments and running them simultaneously on the processing unit, but which obviously takes more RAM to do. Notice, however, that if you drop the precision to int8 from fp16, you use basically the same amount of RAM as whisper.cpp yet it completes in a fraction of the time using batching [0]. Yes, if you check their community integrations sectio", "context": "", "use_case": "speech transcription with diarization", "switched_from": "", "story": "Dell's CES 2026 chat was the most pleasingly un-AI briefing I've had in 5 years"}, {"id": 742327026, "item_id": 46395439, "url": "https://news.ycombinator.com/item?id=46395439", "by": "logicprog", "date": "2025-12-26", "version": null, "stance": "recommend", "quote": "all of the state-of-the-art speech-to-text systems are large-language model based and are significantly faster and better than what we had before.", "excerpt": ">>weather predictions >wrong https://www.noaa.gov/news-release/noaa-deploys-new-generation-of-ai-driven-global-weather-models ? >>OCR >less accurate and efficient than existing solutions, only measures well against other LLMs Where did you hear that? On every benchmark that I've ever seen, VLM's are hilariously better than traditional OCR. Typically, the reason that language models are only compared to other language", "context": "", "use_case": "Speech-to-text", "switched_from": "", "story": "Rob Pike Goes Nuclear over GenAI"}, {"id": 737818784, "item_id": 46113674, "url": "https://news.ycombinator.com/item?id=46113674", "by": "wswope", "date": "2025-12-01", "version": null, "stance": "recommend", "quote": "Whisper-X does speaker-annotated transcripts nicely", "excerpt": "Whisper-X does speaker-annotated transcripts nicely. I\u2019ve used it for running multi-hour TTRPG sessions with friends and it worked hassle-free after setup. https://github.com/m-bain/whisperX", "context": "", "use_case": "transcribing multi-hour TTRPG sessions", "switched_from": "", "story": "How to Attend Meetings"}, {"id": 735539937, "item_id": 45971246, "url": "https://news.ycombinator.com/item?id=45971246", "by": "rahimnathwani", "date": "2025-11-18", "version": null, "stance": "recommend", "quote": "If you need diarization, you can use something like", "excerpt": "For this use case, why not use Whisper to transcribe the audio, and then an LLM to do a second step (summarization or answering questions or whatever)? If you need diarization, you can use something like https://github.com/m-bain/whisperX", "context": "", "use_case": "Speaker diarization", "switched_from": "", "story": "Trying out Gemini 3 Pro with audio transcription and a new pelican benchmark"}]}], "caveats": [{"label": "", "summary": "", "quotes": [{"id": 759079617, "item_id": 47442476, "url": "https://news.ycombinator.com/item?id=47442476", "by": "beveradb", "date": "2026-03-19", "version": null, "stance": "warn", "quote": "my minimum quality bar for the lyrics and sync accuracy in karaoke is much higher than what's achievable with WhisperX / Force Alignment", "excerpt": "This is cool, though for me personally my minimum quality bar for the lyrics and sync accuracy in karaoke is much higher than what's achievable with WhisperX / Force Alignment. I moved on from that approach about 2 years ago in my pursuit of high quality karaoke. If anyone's interested in tooling to generate karaoke videos which unlocks a much higher quality bar, check out my karaoke-gen project - 2 free generation c", "context": "", "use_case": "lyrics sync for karaoke", "switched_from": "", "story": "Nightingale \u2013 open-source karaoke app that works with any song on your computer"}]}], "who": [], "tags": [], "use_cases": ["speaker diarization", "transcription with timing and speakers", "lyrics sync for karaoke", "speech-to-text transcription", "speech transcription with diarization", "subtitle timestamp alignment"], "compared": [{"slug": "nvidia-parakeet", "name": "NVIDIA Parakeet", "co": 2, "switched_from": 0, "switched_to": 0}, {"slug": "whisper", "name": "Whisper", "co": 2, "switched_from": 0, "switched_to": 0}, {"slug": "pyannote", "name": "pyannote", "co": 2, "switched_from": 0, "switched_to": 0}], "makers": [], "threads": [{"url": "https://news.ycombinator.com/item?id=46112906", "title": "How to Attend Meetings", "mentions": 2}, {"url": "https://news.ycombinator.com/item?id=48821576", "title": "Local, CPU-Friendly, High-Quality TTS (Text-to-Speech) with Kokoro", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=47589818", "title": "Cohere Transcribe: Speech Recognition", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=47422942", "title": "Nightingale \u2013 open-source karaoke app that works with any song on your computer", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=47143755", "title": "Show HN: Moonshine Open-Weights STT models \u2013 higher accuracy than WhisperLargev3", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=46527706", "title": "Dell's CES 2026 chat was the most pleasingly un-AI briefing I've had in 5 years", "mentions": 1}], "sentiment_by_month": {"2025-11": {"neutral": 1, "recommend": 1}, "2025-12": {"recommend": 3, "neutral": 1}, "2026-01": {"recommend": 1}, "2026-02": {"neutral": 1}, "2026-03": {"warn": 1, "compare": 1}, "2026-04": {}, "2026-05": {}, "2026-06": {}, "2026-07": {"neutral": 1}, "2026-08": {}, "2026-09": {}, "2026-10": {}}, "versions": [], "version_unnamed": 0, "family_ref": null, "runs_on": null, "lines": [], "quotes": [{"id": 781165521, "item_id": 48822845, "url": "https://news.ycombinator.com/item?id=48822845", "by": "dmayle", "date": "2026-07-07", "version": null, "stance": "neutral", "quote": "I used to keep a version of whisperx around", "excerpt": "Fun... This is something I actually care about... I used to keep a version of whisperx around, because I think it's important to have not just transcription, but also timing and speaker identification (e.g. for subtitles)... It depends on pyannote, though, which has some wierd licensing (and is tougher to script the installs because of it), so I wanted to look at something that both had better transcription, and supp", "context": "", "use_case": "transcription with timing and speakers", "switched_from": "", "story": "Local, CPU-Friendly, High-Quality TTS (Text-to-Speech) with Kokoro"}, {"id": 761467489, "item_id": 47591718, "url": "https://news.ycombinator.com/item?id=47591718", "by": "atoav", "date": "2026-03-31", "version": null, "stance": "compare", "quote": "", "excerpt": "I would try Qwen-ASR: https://qwen.ai/blog?id=qwen3asr See the very bottom of the page for a transcription with timestamps.", "context": "", "use_case": "", "switched_from": "", "story": "Cohere Transcribe: Speech Recognition"}, {"id": 759079617, "item_id": 47442476, "url": "https://news.ycombinator.com/item?id=47442476", "by": "beveradb", "date": "2026-03-19", "version": null, "stance": "warn", "quote": "my minimum quality bar for the lyrics and sync accuracy in karaoke is much higher than what's achievable with WhisperX / Force Alignment", "excerpt": "This is cool, though for me personally my minimum quality bar for the lyrics and sync accuracy in karaoke is much higher than what's achievable with WhisperX / Force Alignment. I moved on from that approach about 2 years ago in my pursuit of high quality karaoke. If anyone's interested in tooling to generate karaoke videos which unlocks a much higher quality bar, check out my karaoke-gen project - 2 free generation c", "context": "", "use_case": "lyrics sync for karaoke", "switched_from": "", "story": "Nightingale \u2013 open-source karaoke app that works with any song on your computer"}, {"id": 754340593, "item_id": 47146287, "url": "https://news.ycombinator.com/item?id=47146287", "by": "theologic", "date": "2026-02-24", "version": null, "stance": "neutral", "quote": "I've been using a Whisper model, specifically WhisperX, to do all my work", "excerpt": "By the way, I've been using a Whisper model, specifically WhisperX, to do all my work, and for whatever reason I just simply was not familiar with the Handy app. I've now downloaded and used it, and what a great suggestion. Thank you for putting it here, along with the direct link to the leaderboard. I can tell that this is now definitely going to be my go-to model and app on all my clients.", "context": "", "use_case": "Speech-to-text transcription", "switched_from": "", "story": "Show HN: Moonshine Open-Weights STT models \u2013 higher accuracy than WhisperLargev3"}, {"id": 744940848, "item_id": 46558803, "url": "https://news.ycombinator.com/item?id=46558803", "by": "satvikpendem", "date": "2026-01-09", "version": null, "stance": "recommend", "quote": "I recommend WhisperX [2], it's the most complete CLI so far", "excerpt": "Batching is essentially running multiple instances at once, ie bundling 8 segments and running them simultaneously on the processing unit, but which obviously takes more RAM to do. Notice, however, that if you drop the precision to int8 from fp16, you use basically the same amount of RAM as whisper.cpp yet it completes in a fraction of the time using batching [0]. Yes, if you check their community integrations sectio", "context": "", "use_case": "speech transcription with diarization", "switched_from": "", "story": "Dell's CES 2026 chat was the most pleasingly un-AI briefing I've had in 5 years"}, {"id": 743070708, "item_id": 46441919, "url": "https://news.ycombinator.com/item?id=46441919", "by": "solid_fuel", "date": "2025-12-30", "version": null, "stance": "neutral", "quote": "whisperX [0] is a library that combines generic whisper speech recognition models with some additional tools", "excerpt": "I've actually done a fair bit of ML work in Elixir, in practice I found: 1) It's generally harder to interface with existing libraries and models (example: whisperX [0] is a library that combines generic whisper speech recognition models with some additional tools like discrete-time-warping to create a transcription with more accurate time stamp alignment - something that was very helpful when generating subtitles. B", "context": "", "use_case": "subtitle timestamp alignment", "switched_from": "", "story": "Go Away Python"}, {"id": 742327026, "item_id": 46395439, "url": "https://news.ycombinator.com/item?id=46395439", "by": "logicprog", "date": "2025-12-26", "version": null, "stance": "recommend", "quote": "all of the state-of-the-art speech-to-text systems are large-language model based and are significantly faster and better than what we had before.", "excerpt": ">>weather predictions >wrong https://www.noaa.gov/news-release/noaa-deploys-new-generation-of-ai-driven-global-weather-models ? >>OCR >less accurate and efficient than existing solutions, only measures well against other LLMs Where did you hear that? On every benchmark that I've ever seen, VLM's are hilariously better than traditional OCR. Typically, the reason that language models are only compared to other language", "context": "", "use_case": "Speech-to-text", "switched_from": "", "story": "Rob Pike Goes Nuclear over GenAI"}, {"id": 737824704, "item_id": 46114044, "url": "https://news.ycombinator.com/item?id=46114044", "by": "satvikpendem", "date": "2025-12-01", "version": null, "stance": "recommend", "quote": "", "excerpt": "Check out Parakeet as well , faster and more accurate in my experience", "context": "", "use_case": "speaker-annotated transcription", "switched_from": "", "story": "How to Attend Meetings"}, {"id": 737818784, "item_id": 46113674, "url": "https://news.ycombinator.com/item?id=46113674", "by": "wswope", "date": "2025-12-01", "version": null, "stance": "recommend", "quote": "Whisper-X does speaker-annotated transcripts nicely", "excerpt": "Whisper-X does speaker-annotated transcripts nicely. I\u2019ve used it for running multi-hour TTRPG sessions with friends and it worked hassle-free after setup. https://github.com/m-bain/whisperX", "context": "", "use_case": "transcribing multi-hour TTRPG sessions", "switched_from": "", "story": "How to Attend Meetings"}, {"id": 735539937, "item_id": 45971246, "url": "https://news.ycombinator.com/item?id=45971246", "by": "rahimnathwani", "date": "2025-11-18", "version": null, "stance": "recommend", "quote": "If you need diarization, you can use something like", "excerpt": "For this use case, why not use Whisper to transcribe the audio, and then an LLM to do a second step (summarization or answering questions or whatever)? If you need diarization, you can use something like https://github.com/m-bain/whisperX", "context": "", "use_case": "Speaker diarization", "switched_from": "", "story": "Trying out Gemini 3 Pro with audio transcription and a new pelican benchmark"}, {"id": 735460032, "item_id": 45966252, "url": "https://news.ycombinator.com/item?id=45966252", "by": "AlexeyBrin", "date": "2025-11-18", "version": null, "stance": "neutral", "quote": "WhisperX with pyannote, but it is not perfect", "excerpt": "WhisperX with pyannote, but it is not perfect, sometime for the same speaker you will get multiple labels. There is no open source fire and forget solution as far as I know.", "context": "", "use_case": "speaker diarization", "switched_from": "", "story": "Ask HN: What do you use for speaker diarization?"}]}