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For Yarn 2+ docs and migration guide, see yarnpkg.com.

Package detail

vosklet

msqr119Apache-2.01.0.3

A speech recognizer that can run on the browser, inspired by vosk-browser

javascript, api, wasm, webassembly, speech-recognizer, vosk, kaldi

readme

Overview

  • A speech recognizer built on Vosk that can be run on the browser, inspired by vosk-browser, but built from scratch and no code taken!
  • Designed with basic/nothrow exception safety
  • See the examples folder for examples on using the API.
  • See API.md for the API reference
  • See test for a developer build script for just the JS

Compared to vosk-browser

  • Support multiple models
  • Has models' storage path management
  • Has models' ID management (for model updates)
  • Has smaller JS size (>3.1MB vs 1.4MB gzipped)
  • Has all related files (pthread worker, audio worklet processor,...) merged
  • Has faster processing time
  • Has shorter from-scratch build time
  • Has more Vosk functions exposed

Basic usage (microphone recognition)

  • Result are logged to the console.
  • Copied from examples/fromMic.html
    <!DOCTYPE html>
    <html>
    <head>
      <script src="https://cdn.jsdelivr.net/gh/msqr1/Vosklet@1.0.3/Vosklet.min.js"></script>
      <script>
        async function start() {
          // Make sure sample rate matches that in the training data
          let ctx = new AudioContext({sampleRate : 16000})
          // Setup mic with correct sample rate
          let micNode = ctx.createMediaStreamSource(await navigator.mediaDevices.getUserMedia({
            video: false,
            audio: {
              echoCancellation: true,
              noiseSuppression: true,
              channelCount: 1,
              sampleRate: 16000
            },
          }))
          // Load Vosklet module, model and recognizer
          let module = await loadVosklet()
          let model = await module.createModel("https://github.com/msqr1/Vosklet/raw/main/examples/en-model.tgz","model","ID")
          let recognizer = await module.createRecognizer(model, 16000)
          // Listen for result and partial result
          recognizer.addEventListener("result", ev => {
            console.log("Result: ", ev.detail)
          })
          recognizer.addEventListener("partialResult", ev => {
            console.log("Partial result: ", ev.detail)
          })
          // Create a transferer node to get audio data on the main thread
          let transferer = await module.createTransferer(ctx, 128 * 150)
          // Recognize data on arrival
          transferer.port.onmessage = ev => {
            recognizer.acceptWaveform(ev.data)
          }
          // Connect to microphone
          micNode.connect(transferer)
        }
      </script>
      <!-- Start and create audio context only as a result of user's action -->
      <button onclick="start()">Start</button>
    </head>
    </html>