How to Use Voice Recognition with Houndify API in JavaScript

Integrate Houndify SDK

• First, make sure you have the houndify-clients npm package. Use npm or yarn to install.

 

• Import the Houndify client into your JavaScript project:

import Houndify from 'houndify';

Configure Houndify Client

• Create a new instance of Houndify. You will need your clientId and clientKey which you get from your Houndify application settings.

 

• Define the user ID and request an authentication signature (more advanced functionality, it can often be a manually set unique user like email).

const houndClient = new Houndify.HoundifyClient({
  clientId: "YOUR_CLIENT_ID",
  clientKey: "YOUR_CLIENT_KEY",
  userId: "unique_user_id",
  requestInfo: {
    UserID: "unique_user_id"
  }
});

Set Up the Audio Recording

• Initialize a new instance of Recorder.js or any compatible audio recording library. This will help capture the audio that will be sent to the Houndify API.

 

• Ensure you handle microphone permissions efficiently, prompting users only when necessary and offering a clear rationale.

const rec = new Recorder({
  encoderPath: 'encoderWorker.min.js',   // Necessary path for some audio encoders
  encoderSampleRate: 16000,               // 16kHz is often used sample rate
  sourceNode: audioContext.createMediaStreamSource(stream)
});

Establish Event Listeners for Recording Control

• Connect your recording handler to UI elements like buttons, ensuring users can easily start and stop recordings.

 

• Add event listeners to these buttons, effectively managing the start and stop of audio capturing.

document.getElementById('start-button').addEventListener('click', () => {
  rec.start().then(() => {
    console.log('Recording started');
  });
});

document.getElementById('stop-button').addEventListener('click', () => {
  rec.stop().then((audioBlob) => {
    console.log('Recording stopped');
    sendToHoundify(audioBlob);
  });
});

Send Audio Data to Houndify

• Utilize Blob data from your recorder to create a stream and send it to the Houndify API.

 

• Handle responses and potential errors from the server appropriately.

function sendToHoundify(audioBlob) {
  const readerStream = new FileReader();
  
  readerStream.onloadend = () => {
    houndClient.voiceSearch({
      audio: readerStream.result,
      onResponse: (response, info) => {
        console.log("Response Received:", response);
      },
      onError: (err) => {
        console.error("Error:", err);
      }
    });
  };
  readerStream.readAsArrayBuffer(audioBlob);
}

Debugging and Logging

• Implement comprehensive error handling within your client to capture and log unexpected responses or network issues.

 

• Use browser developer tools to trace network requests, ensuring audio data is correctly sent and responses are rightfully received.

Optimize Voice Recognitions

• Tweak your audio configurations and Houndify parameters based on testing to achieve optimal voice recognition performance.

 

• Consider the noise environment of your application space, implementing noise cancellation or audio pre-processing as needed.