play original audio in chrome; resample for whisper

This commit is contained in:
makaveli10
2023-06-01 17:06:14 +05:30
parent 0b9fb6c49d
commit cbc6d2c473
+39 -3
View File
@@ -32,6 +32,41 @@ function sendMessageToTab(tabId, data) {
}
/**
* Resamples the audio data to a target sample rate of 16kHz.
* @param {Array|ArrayBuffer|TypedArray} audioData - The input audio data.
* @param {number} [origSampleRate=44100] - The original sample rate of the audio data.
* @returns {Float32Array} The resampled audio data at 16kHz.
*/
function resampleTo16kHZ(audioData, origSampleRate = 44100) {
// Convert the audio data to a Float32Array
const data = new Float32Array(audioData);
// Calculate the desired length of the resampled data
const targetLength = Math.round(data.length * (16000 / origSampleRate));
// Create a new Float32Array for the resampled data
const resampledData = new Float32Array(targetLength);
// Calculate the spring factor and initialize the first and last values
const springFactor = (data.length - 1) / (targetLength - 1);
resampledData[0] = data[0];
resampledData[targetLength - 1] = data[data.length - 1];
// Resample the audio data
for (let i = 1; i < targetLength - 1; i++) {
const index = i * springFactor;
const leftIndex = Math.floor(index).toFixed();
const rightIndex = Math.ceil(index).toFixed();
const fraction = index - leftIndex;
resampledData[i] = data[leftIndex] + (data[rightIndex] - data[leftIndex]) * fraction;
}
// Return the resampled data
return resampledData;
}
/**
* Starts recording audio from the captured tab.
* @param {Object} option - The options object containing the currentTabId.
@@ -89,7 +124,7 @@ async function startRecord(option) {
};
const audioDataCache = [];
const context = new AudioContext({sampleRate: 16000});
const context = new AudioContext();
const mediaStream = context.createMediaStreamSource(stream);
const recorder = context.createScriptProcessor(4096, 1, 1);
@@ -97,11 +132,12 @@ async function startRecord(option) {
if (!context) return;
const inputData = event.inputBuffer.getChannelData(0);
const audioData16kHz = resampleTo16kHZ(inputData, context.sampleRate);
audioDataCache.push(inputData);
// voice activity detection inference
const audioBuffer = new ort.Tensor('float32', inputData, [1, inputData.length]);
const audioBuffer = new ort.Tensor('float32', audioData16kHz, [1, audioData16kHz.length]);
const hh = new ort.Tensor('float32', h, [2, 1, 64]);
const hc = new ort.Tensor('float32', c, [2, 1, 64]);
const feeds = { input: audioBuffer, sr: srate, h: hh, c: hc};
@@ -110,7 +146,7 @@ async function startRecord(option) {
if (doVad) {
vad_infer(feeds)
if (speech_prob > 0.4) {
socket.send(inputData);
socket.send(audioData16kHz);
}
else
console.log("no speech found: " + speech_prob)