feat: integrate rnnoise based service for voice activity (VAD) detection
This commit is contained in:
Andrei Gavrilescu
Saúl Ibarra Corretgé
parent
11d3a343e5
commit
761ac6a730
12
Makefile
12
Makefile
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@ -3,6 +3,7 @@ CLEANCSS = ./node_modules/.bin/cleancss
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DEPLOY_DIR = libs
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LIBJITSIMEET_DIR = node_modules/lib-jitsi-meet/
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LIBFLAC_DIR = node_modules/libflacjs/dist/min/
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RNNOISE_WASM_DIR = node_modules/rnnoise-wasm/dist/
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NODE_SASS = ./node_modules/.bin/node-sass
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NPM = npm
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OUTPUT_DIR = .
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@ -20,7 +21,7 @@ compile:
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clean:
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rm -fr $(BUILD_DIR)
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deploy: deploy-init deploy-appbundle deploy-lib-jitsi-meet deploy-libflac deploy-css deploy-local
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deploy: deploy-init deploy-appbundle deploy-rnnoise-binary deploy-lib-jitsi-meet deploy-libflac deploy-css deploy-local
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deploy-init:
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rm -fr $(DEPLOY_DIR)
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@ -47,6 +48,8 @@ deploy-appbundle:
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$(BUILD_DIR)/analytics-ga.min.map \
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$(BUILD_DIR)/video-blur-effect.min.js \
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$(BUILD_DIR)/video-blur-effect.min.map \
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$(BUILD_DIR)/rnnoise-processor.min.js \
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$(BUILD_DIR)/rnnoise-processor.min.map \
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$(DEPLOY_DIR)
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deploy-lib-jitsi-meet:
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@ -63,6 +66,11 @@ deploy-libflac:
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$(LIBFLAC_DIR)/libflac4-1.3.2.min.js.mem \
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$(DEPLOY_DIR)
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deploy-rnnoise-binary:
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cp \
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$(RNNOISE_WASM_DIR)/rnnoise.wasm \
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$(DEPLOY_DIR)
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deploy-css:
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$(NODE_SASS) $(STYLES_MAIN) $(STYLES_BUNDLE) && \
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$(CLEANCSS) $(STYLES_BUNDLE) > $(STYLES_DESTINATION) ; \
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@ -71,7 +79,7 @@ deploy-css:
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deploy-local:
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([ ! -x deploy-local.sh ] || ./deploy-local.sh)
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dev: deploy-init deploy-css deploy-lib-jitsi-meet deploy-libflac
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dev: deploy-init deploy-css deploy-rnnoise-binary deploy-lib-jitsi-meet deploy-libflac
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$(WEBPACK_DEV_SERVER)
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source-package:
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@ -16413,6 +16413,39 @@
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"inherits": "^2.0.1"
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}
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},
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"rnnoise-wasm": {
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"version": "github:jitsi/rnnoise-wasm#db96d11f175a22ef56c7db1ba9550835b716e615",
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"from": "github:jitsi/rnnoise-wasm#db96d11f175a22ef56c7db1ba9550835b716e615"
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},
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"rollup-plugin-visualizer": {
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"version": "1.1.1",
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"resolved": "https://registry.npmjs.org/rollup-plugin-visualizer/-/rollup-plugin-visualizer-1.1.1.tgz",
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"integrity": "sha512-7xkSKp+dyJmSC7jg2LXqViaHuOnF1VvIFCnsZEKjrgT5ZVyiLLSbeszxFcQSfNJILphqgAEmWAUz0Z4xYScrRw==",
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"optional": true,
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"requires": {
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"mkdirp": "^0.5.1",
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"opn": "^5.4.0",
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"source-map": "^0.7.3",
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"typeface-oswald": "0.0.54"
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},
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"dependencies": {
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"opn": {
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"version": "5.5.0",
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"resolved": "https://registry.npmjs.org/opn/-/opn-5.5.0.tgz",
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"integrity": "sha512-PqHpggC9bLV0VeWcdKhkpxY+3JTzetLSqTCWL/z/tFIbI6G8JCjondXklT1JinczLz2Xib62sSp0T/gKT4KksA==",
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"optional": true,
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"requires": {
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"is-wsl": "^1.1.0"
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}
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},
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"source-map": {
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"version": "0.7.3",
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"resolved": "https://registry.npmjs.org/source-map/-/source-map-0.7.3.tgz",
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"integrity": "sha512-CkCj6giN3S+n9qrYiBTX5gystlENnRW5jZeNLHpe6aue+SrHcG5VYwujhW9s4dY31mEGsxBDrHR6oI69fTXsaQ==",
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"optional": true
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}
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}
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},
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"rsvp": {
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"version": "4.8.5",
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"resolved": "https://registry.npmjs.org/rsvp/-/rsvp-4.8.5.tgz",
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@ -87,6 +87,7 @@
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"react-transition-group": "2.4.0",
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"redux": "4.0.4",
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"redux-thunk": "2.2.0",
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"rnnoise-wasm": "github:jitsi/rnnoise-wasm.git#db96d11f175a22ef56c7db1ba9550835b716e615",
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"styled-components": "3.4.9",
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"util": "0.12.1",
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"uuid": "3.1.0",
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@ -0,0 +1,44 @@
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// @flow
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import { getJitsiMeetGlobalNS, loadScript } from '../base/util';
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let loadRnnoisePromise;
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/**
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* Returns promise that resolves with a RnnoiseProcessor instance.
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*
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* @returns {Promise<RnnoiseProcessor>} - Resolves with the blur effect instance.
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*/
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export function createRnnoiseProcessorPromise() {
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// Subsequent calls should not attempt to load the script multiple times.
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if (!loadRnnoisePromise) {
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loadRnnoisePromise = loadScript('libs/rnnoise-processor.min.js');
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}
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return loadRnnoisePromise.then(() => {
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const ns = getJitsiMeetGlobalNS();
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if (ns?.effects?.rnnoise?.createRnnoiseProcessor) {
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return ns.effects.rnnoise.createRnnoiseProcessor();
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}
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throw new Error('Rnnoise module binding createRnnoiseProcessor not found!');
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});
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}
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/**
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* Get the accepted sample length for the rnnoise library. We might want to expose it with flow libdefs.
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*
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* @returns {number}
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*/
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export function getSampleLength() {
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const ns = getJitsiMeetGlobalNS();
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const rnnoiseSample = ns?.effects?.rnnoise?.RNNOISE_SAMPLE_LENGTH;
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if (!rnnoiseSample) {
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throw new Error('Please call createRnnoiseProcessorPromise first or wait for promise to resolve!');
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}
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return rnnoiseSample;
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}
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@ -0,0 +1,2 @@
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export * from './functions';
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@ -0,0 +1,174 @@
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// @flow
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/**
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* Constant. Rnnoise default sample size, samples of different size won't work.
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*/
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export const RNNOISE_SAMPLE_LENGTH: number = 480;
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/**
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* Constant. Rnnoise only takes inputs of 480 PCM float32 samples thus 480*4.
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*/
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const RNNOISE_BUFFER_SIZE: number = RNNOISE_SAMPLE_LENGTH * 4;
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/**
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* Represents an adaptor for the rnnoise library compiled to webassembly. The class takes care of webassembly
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* memory management and exposes rnnoise functionality such as PCM audio denoising and VAD (voice activity
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* detection) scores.
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*/
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export default class RnnoiseProcessor {
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/**
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* Rnnoise context object needed to perform the audio processing.
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*/
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_context: ?Object;
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/**
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* State flag, check if the instance was destroyed.
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*/
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_destroyed: boolean = false;
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/**
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* WASM interface through which calls to rnnoise are made.
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*/
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_wasmInterface: Object;
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/**
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* WASM dynamic memory buffer used as input for rnnoise processing method.
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*/
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_wasmPcmInput: Object;
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/**
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* The Float32Array index representing the start point in the wasm heap of the _wasmPcmInput buffer.
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*/
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_wasmPcmInputF32Index: number;
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/**
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* WASM dynamic memory buffer used as output for rnnoise processing method.
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*/
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_wasmPcmOutput: Object;
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/**
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* Constructor.
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*
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* @class
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* @param {Object} wasmInterface - WebAssembly module interface that exposes rnnoise functionality.
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*/
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constructor(wasmInterface: Object) {
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// Considering that we deal with dynamic allocated memory employ exception safety strong guarantee
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// i.e. in case of exception there are no side effects.
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try {
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this._wasmInterface = wasmInterface;
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// For VAD score purposes only allocate the buffers once and reuse them
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this._wasmPcmInput = this._wasmInterface._malloc(RNNOISE_BUFFER_SIZE);
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if (!this._wasmPcmInput) {
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throw Error('Failed to create wasm input memory buffer!');
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}
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this._wasmPcmOutput = this._wasmInterface._malloc(RNNOISE_BUFFER_SIZE);
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if (!this._wasmPcmOutput) {
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wasmInterface._free(this._wasmPcmInput);
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throw Error('Failed to create wasm output memory buffer!');
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}
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// The HEAPF32.set function requires an index relative to a Float32 array view of the wasm memory model
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// which is an array of bytes. This means we have to divide it by the size of a float to get the index
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// relative to a Float32 Array.
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this._wasmPcmInputF32Index = this._wasmPcmInput / 4;
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this._context = this._wasmInterface._rnnoise_create();
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} catch (error) {
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// release can be called even if not all the components were initialized.
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this._releaseWasmResources();
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throw error;
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}
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}
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/**
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* Copy the input PCM Audio Sample to the wasm input buffer.
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*
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* @param {Float32Array} pcmSample - Array containing 16 bit format PCM sample stored in 32 Floats .
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* @returns {void}
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*/
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_copyPCMSampleToWasmBuffer(pcmSample: Float32Array) {
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this._wasmInterface.HEAPF32.set(pcmSample, this._wasmPcmInputF32Index);
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}
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/**
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* Convert 32 bit Float PCM samples to 16 bit Float PCM samples and store them in 32 bit Floats.
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*
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* @param {Float32Array} f32Array - Array containing 32 bit PCM samples.
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* @returns {void}
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*/
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_convertTo16BitPCM(f32Array: Float32Array) {
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for (const [ index, value ] of f32Array.entries()) {
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f32Array[index] = value * 0x7fff;
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}
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}
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/**
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* Release resources associated with the wasm context. If something goes downhill here
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* i.e. Exception is thrown, there is nothing much we can do.
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*
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* @returns {void}
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*/
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_releaseWasmResources() {
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// For VAD score purposes only allocate the buffers once and reuse them
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if (this._wasmPcmInput) {
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this._wasmInterface._free(this._wasmPcmInput);
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this._wasmPcmInput = null;
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}
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if (this._wasmPcmOutput) {
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this._wasmInterface._free(this._wasmPcmOutput);
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this._wasmPcmOutput = null;
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}
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if (this._context) {
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this._wasmInterface._rnnoise_destroy(this._context);
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this._context = null;
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}
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}
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/**
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* Release any resources required by the rnnoise context this needs to be called
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* before destroying any context that uses the processor.
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*
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* @returns {void}
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*/
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destroy() {
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// Attempting to release a non initialized processor, do nothing.
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if (this._destroyed) {
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return;
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}
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this._releaseWasmResources();
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this._destroyed = true;
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}
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/**
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* Calculate the Voice Activity Detection for a raw Float32 PCM sample Array.
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* The size of the array must be of exactly 480 samples, this constraint comes from the rnnoise library.
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*
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* @param {Float32Array} pcmFrame - Array containing 32 bit PCM samples.
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* @returns {Float} Contains VAD score in the interval 0 - 1 i.e. 0.90 .
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*/
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calculateAudioFrameVAD(pcmFrame: Float32Array) {
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if (this._destroyed) {
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throw new Error('RnnoiseProcessor instance is destroyed, please create another one!');
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}
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const pcmFrameLength = pcmFrame.length;
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if (pcmFrameLength !== RNNOISE_SAMPLE_LENGTH) {
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throw new Error(`Rnnoise can only process PCM frames of 480 samples! Input sample was:${pcmFrameLength}`);
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}
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this._convertTo16BitPCM(pcmFrame);
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this._copyPCMSampleToWasmBuffer(pcmFrame);
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return this._wasmInterface._rnnoise_process_frame(this._context, this._wasmPcmOutput, this._wasmPcmInput);
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}
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}
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@ -0,0 +1,36 @@
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// @flow
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// Script expects to find rnnoise webassembly binary in the same public path root, otherwise it won't load
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// During the build phase this needs to be taken care of manually
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import rnnoiseWasmInit from 'rnnoise-wasm';
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import RnnoiseProcessor from './RnnoiseProcessor';
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export { RNNOISE_SAMPLE_LENGTH } from './RnnoiseProcessor';
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export type { RnnoiseProcessor };
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let rnnoiseWasmInterface;
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let initializePromise;
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/**
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* Creates a new instance of RnnoiseProcessor.
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*
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* @returns {Promise<RnnoiseProcessor>}
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*/
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export function createRnnoiseProcessor() {
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if (!initializePromise) {
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initializePromise = new Promise((resolve, reject) => {
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rnnoiseWasmInterface = rnnoiseWasmInit({
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onRuntimeInitialized() {
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resolve();
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},
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onAbort(reason) {
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reject(reason);
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}
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});
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});
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}
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return initializePromise.then(
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() => new RnnoiseProcessor(rnnoiseWasmInterface)
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);
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}
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@ -0,0 +1,258 @@
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// @flow
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import { createRnnoiseProcessorPromise, getSampleLength } from '../rnnoise/';
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import EventEmitter from 'events';
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import JitsiMeetJS from '../base/lib-jitsi-meet';
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import logger from './logger';
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import { VAD_SCORE_PUBLISHED } from './VADEvents';
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/**
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* The structure used by TrackVADEmitter to relay a score
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*/
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export type VADScore = {
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/**
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* Device ID associated with the VAD score
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*/
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deviceId: string,
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/**
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* The PCM score from 0 - 1 i.e. 0.60
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*/
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score: number,
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/**
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* Epoch time at which PCM was recorded
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*/
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timestamp: number
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};
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/**
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* Connects an audio JitsiLocalTrack to a RnnoiseProcessor using WebAudio ScriptProcessorNode.
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* Once an object is created audio from the local track flows through the ScriptProcessorNode as raw PCM.
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* The PCM is processed by the rnnoise module and a VAD (voice activity detection) score is obtained, the
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* score is published to consumers via an EventEmitter.
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* After work is done with this service the destroy method needs to be called for a proper cleanup.
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*/
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export default class TrackVADEmitter extends EventEmitter {
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/**
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* The AudioContext instance.
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*/
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_audioContext: AudioContext;
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/**
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* The MediaStreamAudioSourceNode instance.
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*/
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_audioSource: MediaStreamAudioSourceNode;
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/**
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* The ScriptProcessorNode instance.
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*/
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_audioProcessingNode: ScriptProcessorNode;
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/**
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* Buffer to hold residue PCM resulting after a ScriptProcessorNode callback
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*/
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_bufferResidue: Float32Array;
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/**
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* State flag, check if the instance was destroyed
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*/
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_destroyed: boolean = false;
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/**
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* The JitsiLocalTrack instance.
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*/
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_localTrack: Object;
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/**
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* Device ID of the target microphone.
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*/
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_micDeviceId: string;
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/**
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* Callback function that will be called by the ScriptProcessNode with raw PCM data, depending on the set sample
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* rate.
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*/
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_onAudioProcess: (audioEvent: Object) => void;
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/**
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* Sample rate of the ScriptProcessorNode.
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*/
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_procNodeSampleRate: number;
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/**
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* Rnnoise adapter that allows us to calculate VAD score for PCM samples
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*/
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_rnnoiseProcessor: Object;
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/**
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* PCM Sample size expected by the RnnoiseProcessor instance.
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*/
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_rnnoiseSampleSize: number;
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/**
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* Constructor.
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*
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* @param {number} procNodeSampleRate - Sample rate of the ScriptProcessorNode. Possible values 256, 512, 1024,
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* 2048, 4096, 8192, 16384. Passing other values will default to closes neighbor.
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* @param {Object} rnnoiseProcessor - Rnnoise adapter that allows us to calculate VAD score
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* for PCM samples.
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* @param {Object} jitsiLocalTrack - JitsiLocalTrack corresponding to micDeviceId.
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*/
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constructor(procNodeSampleRate: number, rnnoiseProcessor: Object, jitsiLocalTrack: Object) {
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super();
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this._procNodeSampleRate = procNodeSampleRate;
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this._rnnoiseProcessor = rnnoiseProcessor;
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this._localTrack = jitsiLocalTrack;
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this._micDeviceId = jitsiLocalTrack.getDeviceId();
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this._bufferResidue = new Float32Array([]);
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this._audioContext = new AudioContext();
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this._rnnoiseSampleSize = getSampleLength();
|
||||
this._onAudioProcess = this._onAudioProcess.bind(this);
|
||||
|
||||
this._initializeAudioContext();
|
||||
this._connectAudioGraph();
|
||||
|
||||
logger.log(`Constructed VAD emitter for device: ${this._micDeviceId}`);
|
||||
}
|
||||
|
||||
/**
|
||||
* Factory method that sets up all the necessary components for the creation of the TrackVADEmitter.
|
||||
*
|
||||
* @param {string} micDeviceId - Target microphone device id.
|
||||
* @param {number} procNodeSampleRate - Sample rate of the proc node.
|
||||
* @returns {Promise<TrackVADEmitter>} - Promise resolving in a new instance of TrackVADEmitter.
|
||||
*/
|
||||
static async create(micDeviceId: string, procNodeSampleRate: number) {
|
||||
let rnnoiseProcessor = null;
|
||||
let localTrack = null;
|
||||
|
||||
try {
|
||||
logger.log(`Initializing TrackVADEmitter for device: ${micDeviceId}`);
|
||||
|
||||
rnnoiseProcessor = await createRnnoiseProcessorPromise();
|
||||
localTrack = await JitsiMeetJS.createLocalTracks({
|
||||
devices: [ 'audio' ],
|
||||
micDeviceId
|
||||
});
|
||||
|
||||
// We only expect one audio track when specifying a device id.
|
||||
if (!localTrack[0]) {
|
||||
throw new Error(`Failed to create jitsi local track for device id: ${micDeviceId}`);
|
||||
}
|
||||
|
||||
return new TrackVADEmitter(procNodeSampleRate, rnnoiseProcessor, localTrack[0]);
|
||||
} catch (error) {
|
||||
logger.error(`Failed to create TrackVADEmitter for ${micDeviceId} with error: ${error}`);
|
||||
|
||||
if (rnnoiseProcessor) {
|
||||
rnnoiseProcessor.destroy();
|
||||
}
|
||||
|
||||
if (localTrack) {
|
||||
localTrack.stopStream();
|
||||
}
|
||||
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets up the audio graph in the AudioContext.
|
||||
*
|
||||
* @returns {Promise<void>}
|
||||
*/
|
||||
_initializeAudioContext() {
|
||||
this._audioSource = this._audioContext.createMediaStreamSource(this._localTrack.stream);
|
||||
|
||||
// TODO AudioProcessingNode is deprecated check and replace with alternative.
|
||||
// We don't need stereo for determining the VAD score so we create a single chanel processing node.
|
||||
this._audioProcessingNode = this._audioContext.createScriptProcessor(this._procNodeSampleRate, 1, 1);
|
||||
this._audioProcessingNode.onaudioprocess = this._onAudioProcess;
|
||||
}
|
||||
|
||||
/**
|
||||
* ScriptProcessorNode callback, the input parameters contains the PCM audio that is then sent to rnnoise.
|
||||
* Rnnoise only accepts PCM samples of 480 bytes whereas the webaudio processor node can't sample at a multiple
|
||||
* of 480 thus after each _onAudioProcess callback there will remain and PCM buffer residue equal
|
||||
* to _procNodeSampleRate / 480 which will be added to the next sample buffer and so on.
|
||||
*
|
||||
* @param {AudioProcessingEvent} audioEvent - Audio event.
|
||||
* @returns {void}
|
||||
*/
|
||||
_onAudioProcess(audioEvent: Object) {
|
||||
// Prepend the residue PCM buffer from the previous process callback.
|
||||
const inData = audioEvent.inputBuffer.getChannelData(0);
|
||||
const completeInData = [ ...this._bufferResidue, ...inData ];
|
||||
const sampleTimestamp = Date.now();
|
||||
|
||||
let i = 0;
|
||||
|
||||
for (; i + this._rnnoiseSampleSize < completeInData.length; i += this._rnnoiseSampleSize) {
|
||||
const pcmSample = completeInData.slice(i, i + this._rnnoiseSampleSize);
|
||||
const vadScore = this._rnnoiseProcessor.calculateAudioFrameVAD(pcmSample);
|
||||
|
||||
this.emit(VAD_SCORE_PUBLISHED, {
|
||||
timestamp: sampleTimestamp,
|
||||
score: vadScore,
|
||||
deviceId: this._micDeviceId
|
||||
});
|
||||
}
|
||||
|
||||
this._bufferResidue = completeInData.slice(i, completeInData.length);
|
||||
}
|
||||
|
||||
/**
|
||||
* Connects the nodes in the AudioContext to start the flow of audio data.
|
||||
*
|
||||
* @returns {void}
|
||||
*/
|
||||
_connectAudioGraph() {
|
||||
this._audioSource.connect(this._audioProcessingNode);
|
||||
this._audioProcessingNode.connect(this._audioContext.destination);
|
||||
}
|
||||
|
||||
/**
|
||||
* Disconnects the nodes in the AudioContext.
|
||||
*
|
||||
* @returns {void}
|
||||
*/
|
||||
_disconnectAudioGraph() {
|
||||
// Even thought we disconnect the processing node it seems that some callbacks remain queued,
|
||||
// resulting in calls with and uninitialized context.
|
||||
// eslint-disable-next-line no-empty-function
|
||||
this._audioProcessingNode.onaudioprocess = () => {};
|
||||
this._audioProcessingNode.disconnect();
|
||||
this._audioSource.disconnect();
|
||||
}
|
||||
|
||||
/**
|
||||
* Cleanup potentially acquired resources.
|
||||
*
|
||||
* @returns {void}
|
||||
*/
|
||||
_cleanupResources() {
|
||||
logger.debug(`Cleaning up resources for device ${this._micDeviceId}!`);
|
||||
|
||||
this._disconnectAudioGraph();
|
||||
this._localTrack.stopStream();
|
||||
this._rnnoiseProcessor.destroy();
|
||||
}
|
||||
|
||||
/**
|
||||
* Destroy TrackVADEmitter instance (release resources and stop callbacks).
|
||||
*
|
||||
* @returns {void}
|
||||
*/
|
||||
destroy() {
|
||||
if (this._destroyed) {
|
||||
return;
|
||||
}
|
||||
|
||||
logger.log(`Destroying TrackVADEmitter for mic: ${this._micDeviceId}`);
|
||||
this._cleanupResources();
|
||||
this._destroyed = true;
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,7 @@
|
|||
// Event generated by a TrackVADEmitter when it emits a VAD score from rnnoise.
|
||||
// The generated objects are of type VADScore
|
||||
export const VAD_SCORE_PUBLISHED = 'vad-score-published';
|
||||
|
||||
// Event generated by VADReportingService when if finishes creating a VAD report for the monitored devices.
|
||||
// The generated objects are of type Array<VADReportScore>, one score for each monitored device.
|
||||
export const VAD_REPORT_PUBLISHED = 'vad-report-published';
|
||||
|
|
@ -0,0 +1,284 @@
|
|||
// @flow
|
||||
|
||||
import EventEmitter from 'events';
|
||||
import logger from './logger';
|
||||
import TrackVADEmitter from './TrackVADEmitter';
|
||||
import { VAD_SCORE_PUBLISHED, VAD_REPORT_PUBLISHED } from './VADEvents';
|
||||
import type { VADScore } from './TrackVADEmitter';
|
||||
export type { VADScore };
|
||||
|
||||
/**
|
||||
* Sample rate used by TrackVADEmitter, this value determines how often the ScriptProcessorNode is going to call the
|
||||
* process audio function and with what sample size.
|
||||
* Basically lower values mean more callbacks with lower processing times bigger values less callbacks with longer
|
||||
* processing times. This value is somewhere in the middle, so we strike a balance between flooding with callbacks
|
||||
* and processing time. Possible values 256, 512, 1024, 2048, 4096, 8192, 16384. Passing other values will default
|
||||
* to closes neighbor.
|
||||
*/
|
||||
const SCRIPT_NODE_SAMPLE_RATE = 4096;
|
||||
|
||||
/**
|
||||
* Context that contains the emitter and additional information about the device.
|
||||
*/
|
||||
type VADDeviceContext = {
|
||||
|
||||
/**
|
||||
* MediaDeviceInfo for associated context
|
||||
*/
|
||||
deviceInfo: MediaDeviceInfo,
|
||||
|
||||
/**
|
||||
* Array with VAD scores publish from the emitter.
|
||||
*/
|
||||
scoreArray: Array<VADScore>,
|
||||
|
||||
/**
|
||||
* TrackVADEmitter associated with media device
|
||||
*/
|
||||
vadEmitter: TrackVADEmitter
|
||||
};
|
||||
|
||||
/**
|
||||
* The structure used by VADReportingService to relay a score report
|
||||
*/
|
||||
export type VADReportScore = {
|
||||
|
||||
/**
|
||||
* Device ID associated with the VAD score
|
||||
*/
|
||||
deviceId: string,
|
||||
|
||||
/**
|
||||
* The PCM score from 0 - 1 i.e. 0.60
|
||||
*/
|
||||
score: number,
|
||||
|
||||
/**
|
||||
* Epoch time at which PCM was recorded
|
||||
*/
|
||||
timestamp: number
|
||||
};
|
||||
|
||||
|
||||
/**
|
||||
* Voice activity detection reporting service. The service create TrackVADEmitters for the provided devices and
|
||||
* publishes an average of their VAD score over the specified interval via EventEmitter.
|
||||
* The service is not reusable if destroyed a new one needs to be created, i.e. when a new device is added to the system
|
||||
* a new service needs to be created and the old discarded.
|
||||
*/
|
||||
export default class VADReportingService extends EventEmitter {
|
||||
/**
|
||||
* Map containing context for devices currently being monitored by the reporting service.
|
||||
*/
|
||||
_contextMap: Map<string, VADDeviceContext>;
|
||||
|
||||
/**
|
||||
* State flag, check if the instance was destroyed.
|
||||
*/
|
||||
_destroyed: boolean = false;
|
||||
|
||||
/**
|
||||
* Delay at which to publish VAD score for monitored devices.
|
||||
*/
|
||||
_intervalDelay: number;
|
||||
|
||||
/**
|
||||
* Identifier for the interval publishing stats on the set interval.
|
||||
*/
|
||||
_intervalId: ?IntervalID;
|
||||
|
||||
/**
|
||||
* Constructor.
|
||||
*
|
||||
* @param {number} intervalDelay - Delay at which to publish VAD score for monitored devices.
|
||||
* @param {Function} publishScoreCallBack - Function called on the specific interval with the calculated VAD score.
|
||||
*/
|
||||
constructor(intervalDelay: number) {
|
||||
super();
|
||||
this._contextMap = new Map();
|
||||
this._intervalDelay = intervalDelay;
|
||||
|
||||
logger.log(`Constructed VADReportingService with publish interval of: ${intervalDelay}`);
|
||||
}
|
||||
|
||||
/**
|
||||
* Factory methods that creates the TrackVADEmitters for the associated array of devices and instantiates
|
||||
* a VADReportingService.
|
||||
*
|
||||
* @param {Array<MediaDeviceInfo>} micDeviceList - Device list that is monitored inside the service.
|
||||
* @param {number} intervalDelay - Delay at which to publish VAD score for monitored devices.
|
||||
* @param {Function} publishScoreCallBack - Function called on the specific interval with the calculated VAD score.
|
||||
*
|
||||
* @returns {Promise<VADReportingService>}
|
||||
*/
|
||||
static create(micDeviceList: Array<MediaDeviceInfo>, intervalDelay: number) {
|
||||
const vadReportingService = new VADReportingService(intervalDelay);
|
||||
const emitterPromiseArray = [];
|
||||
|
||||
// Create a TrackVADEmitter for each provided audioinput device.
|
||||
for (const micDevice of micDeviceList) {
|
||||
if (micDevice.kind !== 'audioinput') {
|
||||
logger.warn(`Provided device ${micDevice.label} -> ${micDevice.deviceId}, is not audioinput ignoring!`);
|
||||
|
||||
return;
|
||||
}
|
||||
|
||||
logger.log(`Initializing VAD context for mic: ${micDevice.label} -> ${micDevice.deviceId}`);
|
||||
|
||||
const emitterPromise = TrackVADEmitter.create(micDevice.deviceId, SCRIPT_NODE_SAMPLE_RATE).then(emitter => {
|
||||
emitter.on(VAD_SCORE_PUBLISHED, vadReportingService._devicePublishVADScore.bind(vadReportingService));
|
||||
|
||||
return {
|
||||
vadEmitter: emitter,
|
||||
deviceInfo: micDevice,
|
||||
scoreArray: []
|
||||
};
|
||||
});
|
||||
|
||||
emitterPromiseArray.push(emitterPromise);
|
||||
}
|
||||
|
||||
// Once all the TrackVADEmitter promises are resolved check if all of them resolved properly if not reject
|
||||
// the promise and clear the already created emitters.
|
||||
// $FlowFixMe - allSettled is not part of flow prototype even though it's a valid Promise function
|
||||
return Promise.allSettled(emitterPromiseArray).then(outcomeArray => {
|
||||
const vadContextArray = [];
|
||||
const rejectedEmitterPromiseArray = [];
|
||||
|
||||
for (const outcome of outcomeArray) {
|
||||
if (outcome.status === 'fulfilled') {
|
||||
vadContextArray.push(outcome.value);
|
||||
} else {
|
||||
// Promise was rejected.
|
||||
logger.error(`Create TrackVADEmitter promise failed with ${outcome.reason}`);
|
||||
|
||||
rejectedEmitterPromiseArray.push(outcome);
|
||||
}
|
||||
}
|
||||
|
||||
// Check if there were any rejected promises and clear the already created ones list.
|
||||
if (rejectedEmitterPromiseArray.length > 0) {
|
||||
logger.error('Cleaning up remaining VADDeviceContext, due to create fail!');
|
||||
|
||||
for (const context of vadContextArray) {
|
||||
context.vadEmitter.destroy();
|
||||
}
|
||||
|
||||
// Reject create promise if one emitter failed to instantiate, we might one just ignore it,
|
||||
// leaving it like this for now
|
||||
throw new Error('Create VADReportingService failed due to TrackVADEmitter creation issues!');
|
||||
}
|
||||
|
||||
vadReportingService._setVADContextArray(vadContextArray);
|
||||
vadReportingService._startPublish();
|
||||
|
||||
return vadReportingService;
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Destroy TrackVADEmitters and clear the context map.
|
||||
*
|
||||
* @returns {void}
|
||||
*/
|
||||
_clearContextMap() {
|
||||
for (const vadContext of this._contextMap.values()) {
|
||||
vadContext.vadEmitter.destroy();
|
||||
}
|
||||
this._contextMap.clear();
|
||||
}
|
||||
|
||||
/**
|
||||
* Set the watched device contexts.
|
||||
*
|
||||
* @param {Array<VADDeviceContext>} vadContextArray - List of mics.
|
||||
* @returns {void}
|
||||
*/
|
||||
_setVADContextArray(vadContextArray: Array<VADDeviceContext>): void {
|
||||
for (const vadContext of vadContextArray) {
|
||||
this._contextMap.set(vadContext.deviceInfo.deviceId, vadContext);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Start the setInterval reporting process.
|
||||
*
|
||||
* @returns {void}.
|
||||
*/
|
||||
_startPublish() {
|
||||
logger.log('VADReportingService started publishing.');
|
||||
this._intervalId = setInterval(() => {
|
||||
this._reportVadScore();
|
||||
}, this._intervalDelay);
|
||||
}
|
||||
|
||||
/**
|
||||
* Function called at set interval with selected compute. The result will be published on the set callback.
|
||||
*
|
||||
* @returns {void}
|
||||
*/
|
||||
_reportVadScore() {
|
||||
const vadComputeScoreArray = [];
|
||||
const computeTimestamp = Date.now();
|
||||
|
||||
// Go through each device and compute cumulated VAD score.
|
||||
|
||||
for (const [ deviceId, vadContext ] of this._contextMap) {
|
||||
const nrOfVADScores = vadContext.scoreArray.length;
|
||||
let vadSum = 0;
|
||||
|
||||
vadContext.scoreArray.forEach(vadScore => {
|
||||
vadSum += vadScore.score;
|
||||
});
|
||||
|
||||
// TODO For now we just calculate the average score for each device, more compute algorithms will be added.
|
||||
const avgVAD = vadSum / nrOfVADScores;
|
||||
|
||||
vadContext.scoreArray = [];
|
||||
|
||||
vadComputeScoreArray.push({
|
||||
timestamp: computeTimestamp,
|
||||
score: avgVAD,
|
||||
deviceId
|
||||
});
|
||||
}
|
||||
|
||||
this.emit(VAD_REPORT_PUBLISHED, vadComputeScoreArray);
|
||||
}
|
||||
|
||||
/**
|
||||
* Callback method passed to vad emitters in order to publish their score.
|
||||
*
|
||||
* @param {VADScore} vadScore - Mic publishing the score.
|
||||
* @returns {void}
|
||||
*/
|
||||
_devicePublishVADScore(vadScore: VADScore) {
|
||||
const context = this._contextMap.get(vadScore.deviceId);
|
||||
|
||||
if (context) {
|
||||
context.scoreArray.push(vadScore);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Destroy the VADReportingService, stops the setInterval reporting, destroys the emitters and clears the map.
|
||||
* After this call the instance is no longer usable.
|
||||
*
|
||||
* @returns {void}.
|
||||
*/
|
||||
destroy() {
|
||||
if (this._destroyed) {
|
||||
return;
|
||||
}
|
||||
|
||||
logger.log('Destroying VADReportingService.');
|
||||
|
||||
if (this._intervalId) {
|
||||
clearInterval(this._intervalId);
|
||||
this._intervalId = null;
|
||||
}
|
||||
this._clearContextMap();
|
||||
this._destroyed = true;
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,5 @@
|
|||
// @flow
|
||||
|
||||
import { getLogger } from '../base/logging/functions';
|
||||
|
||||
export default getLogger('features/vad-reporter');
|
||||
|
|
@ -214,16 +214,46 @@ module.exports = [
|
|||
},
|
||||
performance: getPerformanceHints(5 * 1024)
|
||||
}),
|
||||
|
||||
// Because both video-blur-effect and rnnoise-processor modules are loaded
|
||||
// in a lazy manner using the loadScript function with a hard coded name,
|
||||
// i.e.loadScript('libs/rnnoise-processor.min.js'), webpack dev server
|
||||
// won't know how to properly load them using the default config filename
|
||||
// and sourceMapFilename parameters which target libs without .min in dev
|
||||
// mode. Thus we change these modules to have the same filename in both
|
||||
// prod and dev mode.
|
||||
Object.assign({}, config, {
|
||||
entry: {
|
||||
'video-blur-effect': './react/features/stream-effects/blur/index.js'
|
||||
},
|
||||
output: Object.assign({}, config.output, {
|
||||
library: [ 'JitsiMeetJS', 'app', 'effects' ],
|
||||
libraryTarget: 'window'
|
||||
libraryTarget: 'window',
|
||||
filename: '[name].min.js',
|
||||
sourceMapFilename: '[name].min.map'
|
||||
}),
|
||||
performance: getPerformanceHints(1 * 1024 * 1024)
|
||||
}),
|
||||
|
||||
Object.assign({}, config, {
|
||||
entry: {
|
||||
'rnnoise-processor': './react/features/stream-effects/rnnoise/index.js'
|
||||
},
|
||||
node: {
|
||||
// Emscripten generated glue code "rnnoise.js" expects node fs module,
|
||||
// we need to specify this parameter so webpack knows how to properly
|
||||
// interpret it when encountered.
|
||||
fs: 'empty'
|
||||
},
|
||||
output: Object.assign({}, config.output, {
|
||||
library: [ 'JitsiMeetJS', 'app', 'effects', 'rnnoise' ],
|
||||
libraryTarget: 'window',
|
||||
filename: '[name].min.js',
|
||||
sourceMapFilename: '[name].min.map'
|
||||
}),
|
||||
performance: getPerformanceHints(30 * 1024)
|
||||
}),
|
||||
|
||||
Object.assign({}, config, {
|
||||
entry: {
|
||||
'external_api': './modules/API/external/index.js'
|
||||
|
|
@ -249,7 +279,8 @@ function devServerProxyBypass({ path }) {
|
|||
if (path.startsWith('/css/') || path.startsWith('/doc/')
|
||||
|| path.startsWith('/fonts/') || path.startsWith('/images/')
|
||||
|| path.startsWith('/sounds/')
|
||||
|| path.startsWith('/static/')) {
|
||||
|| path.startsWith('/static/')
|
||||
|| path.endsWith('.wasm')) {
|
||||
return path;
|
||||
}
|
||||
|
||||
|
|
@ -258,7 +289,7 @@ function devServerProxyBypass({ path }) {
|
|||
/* eslint-disable array-callback-return, indent */
|
||||
|
||||
if ((Array.isArray(configs) ? configs : Array(configs)).some(c => {
|
||||
if (path.startsWith(c.output.publicPath)) {
|
||||
if (path.startsWith(c.output.publicPath)) {
|
||||
if (!minimize) {
|
||||
// Since webpack-dev-server is serving non-minimized
|
||||
// artifacts, serve them even if the minimized ones are
|
||||
|
|
|
|||
Loading…
Reference in New Issue