148 lines
3.9 KiB
JavaScript
148 lines
3.9 KiB
JavaScript
/**
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* Captures audio from the active tab in Google Chrome.
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* @returns {Promise<MediaStream>} A promise that resolves with the captured audio stream.
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*/
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function captureTabAudio() {
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return new Promise((resolve) => {
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chrome.tabCapture.capture(
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{
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audio: true,
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video: false,
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},
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(stream) => {
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resolve(stream);
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}
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);
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});
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}
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/**
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* Sends a message to a specific tab in Google Chrome.
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* @param {number} tabId - The ID of the tab to send the message to.
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* @param {any} data - The data to be sent as the message.
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* @returns {Promise<any>} A promise that resolves with the response from the tab.
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*/
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function sendMessageToTab(tabId, data) {
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return new Promise((resolve) => {
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chrome.tabs.sendMessage(tabId, data, (response) => {
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resolve(response);
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});
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});
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}
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/**
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* Starts recording audio from the captured tab.
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* @param {Object} option - The options object containing the currentTabId.
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*/
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async function startRecord(option) {
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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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// call when the stream inactive
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stream.oninactive = () => {
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window.close();
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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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socket.onopen = function(e) {
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socket.send("handshake");
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};
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socket.onmessage = async (event) => {
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// console.log(event.data);
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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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});
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};
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const audioDataCache = [];
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const context = new AudioContext({sampleRate: 16000});
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const mediaStream = context.createMediaStreamSource(stream);
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const recorder = context.createScriptProcessor(4096, 1, 1);
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recorder.onaudioprocess = async (event) => {
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if (!context) return;
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const inputData = event.inputBuffer.getChannelData(0);
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audioDataCache.push(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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// Prevent page mute
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mediaStream.connect(recorder);
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recorder.connect(context.destination);
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mediaStream.connect(context.destination);
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} else {
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window.close();
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}
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}
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/**
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* Listener for incoming messages from the extension's background script.
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* @param {Object} request - The message request object.
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* @param {Object} sender - The sender object containing information about the message sender.
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* @param {Function} sendResponse - The function to send a response back to the message sender.
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*/
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chrome.runtime.onMessage.addListener(async (request, sender, sendResponse) => {
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const { type, data } = request;
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switch (type) {
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case "start_capture":
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await startRecord(data);
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break;
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default:
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break;
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}
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sendResponse({});
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});
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