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Vosk: offline speech recognition toolkit, README overview

Public record src_01M6V5KVEB336053WGZ1R7RW55, revision 1. Source and rights labels remain attached. Linked media has not been viewed by opening this page.

# Vosk: offline speech recognition toolkit, README overview

- id: src_01M6V5KVEB336053WGZ1R7RW55
- type: source · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T13 · tags: none
- updated: 2026-11-07T14:11:49.291Z
- url: https://veyrul.com/sources/src_01M6V5KVEB336053WGZ1R7RW55

The README presents Vosk as an offline open source speech recognition toolkit for 20+ languages and dialects.

Source: https://github.com/alphacep/vosk-api

What it supplies: The README presents Vosk as an offline open source speech recognition toolkit for 20+ languages and dialects.

Useful for: - Add offline speech recognition to chatbots, smart home devices or virtual assistants.
- Create subtitles or transcribe lectures and interviews.
- Run on devices from a Raspberry Pi or phone up to large clusters.

First action: - Go to the Vosk website for installation instructions and examples; the README gives no commands.
- Choose a binding for your language, such as Python, Java or Node.JS.
- Pick a small model for your language.

Prerequisites and limits: The README gives no version or system prerequisites. It describes models as small, about 50 Mb, with a streaming API.

- The README is a short overview; install steps, model downloads and accuracy figures are not in it.
- Language coverage is as listed by the README and may have changed.

The README text states no licence, so check the repository and model terms before use.

Written from the README text only. Statements are as the README gives them; nothing was installed or run.
Based on README text only; the Vosk website, model list and code were not read. No install or run was made.

Source inspected: https://raw.githubusercontent.com/alphacep/vosk-api/4ab9821510b488efb7740094714a130bd3545e90/README.md ; 1107 bytes ; sha256 5f56ab2addced6c3655d22dbeeaf05dd5fc75ab9aa8e5e6a9f18b622fe68e5bb ; 7 exact pinned excerpts in the draft pin map

```json
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  "archived": null,
  "revision": {
    "ref": "commit 4ab9821510b488efb7740094714a130bd3545e90",
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    "source_url": "https://raw.githubusercontent.com/alphacep/vosk-api/4ab9821510b488efb7740094714a130bd3545e90/README.md"
  },
  "checked_at": "2026-11-07T10:50:50.049Z",
  "parent_url": null,
  "usefulness": "- Add offline speech recognition to chatbots, smart home devices or virtual assistants.\n- Create subtitles or transcribe lectures and interviews.\n- Run on devices from a Raspberry Pi or phone up to large clusters.",
  "source_type": "repository",
  "availability": "available",
  "dependencies": [],
  "source_owner": "Alpha Cephei (declared repository namespace)",
  "next_check_at": null,
  "successor_url": null,
  "hardware_notes": null,
  "known_limitations": [
    "The README gives no version or system prerequisites. It describes models as small, about 50 Mb, with a streaming API.\n\n- The README is a short overview; install steps, model downloads and accuracy figures are not in it.\n- Language coverage is as listed by the README and may have changed.\n\nThe README text states no licence, so check the repository and model terms before use.\n\nWritten from the README text only. Statements are as the README gives them; nothing was installed or run.\nBased on README text only; the Vosk website, model list and code were not read. No install or run was made.",
    "Rendered README text of the exact archived capture at the pinned commit, read in full by the author; no media viewed or heard; nothing executed or installed.",
    "Source-documented steps; execution not performed. Internal affiliated review is not independent validation."
  ],
  "upstream_updated_at": null
}
```

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=permitted training=unknown · Only the team-authored original attributed summary and links are covered. Upstream papers, tutorials, code, models, weights and media retain their separate terms; no source-text/media redistribution right is implied.

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