add voice activity detection
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@@ -170,7 +170,8 @@ async function stopCapture() {
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if (optionTabId) {
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if (optionTabId) {
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res = await sendMessageToTab(currentTabId, {
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res = await sendMessageToTab(currentTabId, {
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type: "STOP"
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type: "STOP",
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data: { currentTabId: currentTabId },
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});
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});
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await removeChromeTab(optionTabId);
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await removeChromeTab(optionTabId);
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}
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}
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@@ -188,3 +189,15 @@ chrome.runtime.onMessage.addListener((message) => {
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stopCapture();
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stopCapture();
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}
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}
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});
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});
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/**
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* Listens for if the tab is reloaded.
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* @param {Object} message - The message received from the runtime.
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*/
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chrome.tabs.onUpdated.addListener(async (tabId, changeInfo, tab) => {
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if (changeInfo.status === 'complete') {
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await executeScriptInTab(tabId, "content.js");
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await delayExecution(500);
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}
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});
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@@ -4,7 +4,9 @@
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"name": "Audio Transcription",
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"name": "Audio Transcription",
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"version": "1.0.0",
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"version": "1.0.0",
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"description": "This extension captures the audio on the current tab, sends it to a server for transcription and shows the transcription in Real-time.",
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"description": "This extension captures the audio on the current tab, sends it to a server for transcription and shows the transcription in Real-time.",
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"content_security_policy": {
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"extension_pages": "script-src 'self' 'wasm-unsafe-eval'; object-src 'self';"
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},
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"options_page": "options.html",
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"options_page": "options.html",
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"background": {
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"background": {
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"service_worker": "background.js"
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"service_worker": "background.js"
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@@ -4,15 +4,14 @@
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<head>
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<head>
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<meta charset="UTF-8">
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<meta charset="UTF-8">
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<title>Audio Transcription Options</title>
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<title>Audio Transcription Options</title>
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<script src="options.js"></script>
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<meta http-equiv="X-UA-Compatible" content="IE=edge">
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<meta http-equiv="X-UA-Compatible" content="IE=edge">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<link rel="stylesheet" href="options.css" type="text/css">
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<link rel="stylesheet" href="style.css" type="text/css">
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</head>
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</head>
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<body>
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<body>
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<div class="header"><img src="./collabora.png"/> <h1>Audio Transcription</h1></div>
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<script src="ort.min.js"></script>
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<div class="button" id="stop">Stop Capture</div>
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<script src="options.js"></script>
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</body>
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</body>
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</html>
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</html>
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@@ -38,12 +38,43 @@ function sendMessageToTab(tabId, data) {
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*/
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*/
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async function startRecord(option) {
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async function startRecord(option) {
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const stream = await captureTabAudio();
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const stream = await captureTabAudio();
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var doVad = true;
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if (stream) {
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if (stream) {
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// call when the stream inactive
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// call when the stream inactive
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stream.oninactive = () => {
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stream.oninactive = () => {
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window.close();
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window.close();
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};
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};
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// create onnx model
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// initialize onnx model
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const session = await ort.InferenceSession.create('./silero_vad.onnx');
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var h = new Array(128);
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for (let i = 0; i < h.length; i++) {
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h[i] = 0;
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}
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var c = new Array(128);
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for (let i = 0; i < h.length; i++) {
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c[i] = 0;
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}
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const sr = new BigInt64Array(1)
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sr[0] = BigInt(16000);
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const srate = new ort.Tensor('int64', sr, [1]);
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let speech_prob = undefined;
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const vad_infer = async (feed_dict) => {
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// feed inputs and run
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try{
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const results = await session.run(feed_dict);
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// update states
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h = results.hn.data
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c = results.cn.data
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speech_prob = results.output.data
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} catch(e) {
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console.log(e)
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}
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}
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const socket = new WebSocket("ws://localhost:9090/");
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const socket = new WebSocket("ws://localhost:9090/");
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socket.onopen = function(e) {
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socket.onopen = function(e) {
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socket.send("handshake");
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socket.send("handshake");
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@@ -51,7 +82,8 @@ async function startRecord(option) {
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socket.onmessage = async (event) => {
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socket.onmessage = async (event) => {
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// console.log(event.data);
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// console.log(event.data);
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await sendMessageToTab(option.currentTabId, {
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res = await sendMessageToTab(option.currentTabId, {
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type: "transcript",
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data: event.data,
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data: event.data,
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});
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});
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};
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};
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@@ -67,7 +99,22 @@ async function startRecord(option) {
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const inputData = event.inputBuffer.getChannelData(0);
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const inputData = event.inputBuffer.getChannelData(0);
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audioDataCache.push(inputData);
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audioDataCache.push(inputData);
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socket.send(inputData);
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// voice activity detection inference
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const audioBuffer = new ort.Tensor('float32', inputData, [1, inputData.length]);
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const hh = new ort.Tensor('float32', h, [2, 1, 64]);
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const hc = new ort.Tensor('float32', c, [2, 1, 64]);
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const feeds = { input: audioBuffer, sr: srate, h: hh, c: hc};
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// feed inputs and run
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if (doVad) {
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vad_infer(feeds)
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if (speech_prob > 0.4) {
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socket.send(inputData);
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}
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else
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console.log("no speech found: " + speech_prob)
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}
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};
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};
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// Prevent page mute
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// Prevent page mute
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