{"data":{"slug":"linto-ai-whisper-timestamped","name":"whisper-timestamped","tagline":"Multilingual Automatic Speech Recognition with word-level timestamps and confidence","github_url":"https://github.com/linto-ai/whisper-timestamped","owner":"linto-ai","repo":"whisper-timestamped","owner_avatar_url":"https://avatars.githubusercontent.com/u/36000254?v=4","primary_language":"Python","stars":2845,"forks":209,"topics":["asr","attention-is-all-you-need","attention-mechanism","attention-model","attention-network","attention-seq2seq","attention-visualization","deep-learning","machine-learning","multilingual-models","python","python3","pytorch","speaker-diarization","speech","speech-processing","speech-recognition","speech-to-text","transformers","whisper"],"archived":false,"github_pushed_at":"2026-08-17T06:41:29+00:00","maintenance_label":"Steady","stars_delta_30d":13,"url":"https://www.graphcanon.com/tools/linto-ai-whisper-timestamped","markdown_url":"https://www.graphcanon.com/tools/linto-ai-whisper-timestamped.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/linto-ai-whisper-timestamped","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=linto-ai-whisper-timestamped","description":"Multilingual Automatic Speech Recognition with word-level timestamps and confidence","homepage_url":null,"license":"AGPL-3.0","open_issues":48,"watchers":35,"ai_summary":"A library for speech recognition that adds fine-grained timestamping and confidence to the output of OpenAI's Whisper model.","readme_excerpt":"### First installation\n\nRequirements:\n* `python3` (version higher or equal to 3.7, at least 3.9 is recommended)\n* `ffmpeg` (see instructions for installation on the [whisper repository](https://github.com/openai/whisper))\n\nYou can install `whisper-timestamped` either by using pip:\n```bash\npip3 install whisper-timestamped\n```\n\nor by cloning this repository and running installation:\n```bash\ngit clone https://github.com/linto-ai/whisper-timestamped\ncd whisper-timestamped/\npython3 setup.py install\n```\n\n#### Additional packages that might be needed\n\nIf you want to plot alignment between audio timestamps and words (as in [this section](#plot-of-word-alignment)), you also need matplotlib:\n```bash\npip3 install matplotlib\n```\n\nIf you want to use VAD option (Voice Activity Detection before running Whisper model), you also need torchaudio and onnxruntime:\n```bash\npip3 install onnxruntime torchaudio\n```\n\nIf you want to use finetuned Whisper models from the Hugging Face Hub, you also need transformers:\n```bash\npip3 install transformers\n```\n\n#### Docker\n\nA docker image of about 9GB can be built using:\n```bash\ngit clone https://github.com/linto-ai/whisper-timestamped\ncd whisper-timestamped/\ndocker build -t whisper_timestamped:latest .\n```\n\n---\n\n### Light installation for CPU\n\nIf you don't have a GPU (or don't want to use it), then you don't need to install the CUDA dependencies. You should then just install a light version of torch **before** installing whisper-timestamped, for instance as follows:\n```bash\npip3 install \\\n     torch==1.13.1+cpu \\\n     torchaudio==0.13.1+cpu \\\n     -f https://download.pytorch.org/whl/torch_stable.html\n```\n\nA specific docker image of about 3.5GB can also be built using:\n```bash\ngit clone https://github.com/linto-ai/whisper-timestamped\ncd whisper-timestamped/\ndocker build -t whisper_timestamped_cpu:latest -f Dockerfile.cpu .\n```","github_created_at":"2023-01-13T11:30:19+00:00","created_at":"2026-07-11T12:16:46.784284+00:00","updated_at":"2026-09-20T07:18:41.302896+00:00","categories":[{"slug":"speech-audio","name":"Speech & Audio","url":"https://www.graphcanon.com/categories/speech-audio","markdown_url":"https://www.graphcanon.com/categories/speech-audio.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/speech-audio"}],"tags":[{"slug":"asr","name":"asr"},{"slug":"attention-mechanism","name":"attention-mechanism"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"multilingual-models","name":"multilingual-models"},{"slug":"python3","name":"python3"},{"slug":"pytorch","name":"pytorch"},{"slug":"speech-recognition","name":"speech recognition"},{"slug":"transformers","name":"transformers"}],"trust":{"provenance":{"is_fork":false,"github_id":588543419,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T07:18:38.917Z","maintenance":{"label":"Steady","score":60,"methodology":"github_public_v1","releases_90d":0,"days_since_push":34,"last_release_at":"2025-09-09T07:04:36Z","stars_delta_30d":13,"open_issues_delta_30d":-1},"security_summary":{"status":"ok","scanner":"osv@v1","low_count":0,"high_count":0,"last_scan_at":"2026-07-11T12:16:49.055Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T07:18:39.950Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-09-20T07:18:39.950Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-09-20T07:18:39.950Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-09-20T07:18:39.950Z"},"license_spdx":{"value":"AGPL-3.0","source":"github.license","observed_at":"2026-09-20T07:18:39.950Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you need precise timestamping for each spoken word in speech recognition output.","For multilingual speech processing where accurate time alignment between audio and transcriptions is essential."],"when_not_to_use":["Avoid if your project requires minimal dependencies or a smaller footprint, as it includes several external libraries like matplotlib and transformers.","Not suitable for real-time applications where low latency is crucial due to the additional overhead of timestamp generation and confidence scoring."],"source":"enrich:decision_facts","observed_at":"2026-07-17T01:12:14.825Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"whisper-timestamped is a Python library that extends OpenAI's Whisper model with word-level timestamps and confidence scoring."}]}}