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Open-source tools & agent skills to build the things you’re paying for.

Build offline speech recognition into apps, devices, and custom workflows.

Added 2026-10-07
Replaces
GitHub

What you can build

  • Build a local batch tool that accepts lecture audio and saves the recognized words as a plain-text transcript.
  • Build a caption panel that consumes microphone audio through the streaming API and displays recognition results as they arrive.
  • Build a review tool that turns interview audio into transcript segments labeled with Vosk's speaker-identification results.
  • Build a command interface that uses configurable vocabulary to recognize a fixed set of spoken phrases and map each phrase to an application action.
  • Build an intake tool with a manual language selector that transcribes voice notes and stores each transcript with its selected language for later search.

Try this prompt

Build an end-to-end offline voice-command prototype in a language binding documented by Vosk. Accept microphone audio, recognize phrases using configurable vocabulary, and map a small set of exact phrases to visible actions in a simple app. Show recognition results and unknown phrases without triggering actions. Keep the original audio and recognition log until the user explicitly clears them. Include setup notes and a small test plan; do not add cloud speech services.

Get started

  1. Choose a binding

    Vosk documents bindings for Python, Java, Node.js, C#, C++, Rust, Go, and others. Pick the one suited to your application and follow the installation guide and examples on the official Vosk website: https://alphacephei.com/vosk.

  2. Select a language model

    Choose a model for the language you need using the official Vosk documentation. The README describes models as small (50 Mb); allow for model storage and the compute resources of your chosen device.

License & notes

Apache-2.0The repository is Apache-2.0 licensed; commercial use is permitted, subject to license obligations such as retaining notices when distributing the work. Vosk describes offline recognition with local models, so the documented workflow does not require a per-request speech API. Budget for device or server compute, model storage, and any hosting you choose; no prices are supplied. Check the terms for any selected model separately.

  • Recognition depends on the selected language model and available local compute; the README provides no accuracy guarantee.
  • Vosk provides recognition components, not application storage, caption presentation, or business rules; implement those in your adaptation.
  • Check the selected model's terms separately; the supplied license evidence covers the repository, not model licensing.

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