Repository: kdavis-mozilla/vad.js
Branch: master
Commit: 99f459c71361
Files: 4
Total size: 10.5 KB
Directory structure:
gitextract_z7ivhd_8/
├── LICENSE
├── README.md
├── bower.json
└── lib/
└── vad.js
================================================
FILE CONTENTS
================================================
================================================
FILE: LICENSE
================================================
Copyright (c) 2015, Kelly Davis
All rights reserved.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice, this
list of conditions and the following disclaimer in the documentation and/or
other materials provided with the distribution.
* Neither the name of the {organization} nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
================================================
FILE: README.md
================================================
# Voice activity detection in Javascript
__vad.js__ is a small Javascript library for voice activity detection.
### Quick Start
```html
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<title>VAD Test</title>
<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1" />
</head>
<body>
<script type="text/javascript" src="lib/vad.js"></script>
<script type="text/javascript">
// Create AudioContext
window.AudioContext = window.AudioContext || window.webkitAudioContext;
var audioContext = new AudioContext();
// Define function called by getUserMedia
function startUserMedia(stream) {
// Create MediaStreamAudioSourceNode
var source = audioContext.createMediaStreamSource(stream);
// Setup options
var options = {
source: source,
voice_stop: function() {console.log('voice_stop');},
voice_start: function() {console.log('voice_start');}
};
// Create VAD
var vad = new VAD(options);
}
// Ask for audio device
navigator.getUserMedia = navigator.getUserMedia ||
navigator.mozGetUserMedia ||
navigator.webkitGetUserMedia;
navigator.getUserMedia({audio: true}, startUserMedia, function(e) {
console.log("No live audio input in this browser: " + e);
});
</script>
</body>
</html>
```
### Tested - Browser
* Firefox 45.0a1+
##Author
* Kelly Davis kdavis@mozilla.com
* Mark Panaghiston https://github.com/thepag
##Thanks
The code is based on the following implementations:
+ https://github.com/happyworm/Playful-Demos
##Contribution
Any contribution will be welcome!
================================================
FILE: bower.json
================================================
{
"name": "vad.js",
"homepage": "https://github.com/kdavis-mozilla/vad.js",
"authors": [
"Kelly Davis <kdavis@mozilla.com>"
],
"description": "Voice activity detection in Javascript",
"main": "lib/vad.js",
"moduleType": [],
"keywords": [
"vad",
"voice",
"activity",
"detection"
],
"license": "BSD-3-Clause",
"ignore": [
"**/.*",
"node_modules",
"bower_components",
"test",
"tests"
]
}
================================================
FILE: lib/vad.js
================================================
(function(window) {
var VAD = function(options) {
// Default options
this.options = {
fftSize: 512,
bufferLen: 512,
voice_stop: function() {},
voice_start: function() {},
smoothingTimeConstant: 0.99,
energy_offset: 1e-8, // The initial offset.
energy_threshold_ratio_pos: 2, // Signal must be twice the offset
energy_threshold_ratio_neg: 0.5, // Signal must be half the offset
energy_integration: 1, // Size of integration change compared to the signal per second.
filter: [
{f: 200, v:0}, // 0 -> 200 is 0
{f: 2000, v:1} // 200 -> 2k is 1
],
source: null,
context: null
};
// User options
for(var option in options) {
if(options.hasOwnProperty(option)) {
this.options[option] = options[option];
}
}
// Require source
if(!this.options.source)
throw new Error("The options must specify a MediaStreamAudioSourceNode.");
// Set this.options.context
this.options.context = this.options.source.context;
// Calculate time relationships
this.hertzPerBin = this.options.context.sampleRate / this.options.fftSize;
this.iterationFrequency = this.options.context.sampleRate / this.options.bufferLen;
this.iterationPeriod = 1 / this.iterationFrequency;
var DEBUG = true;
if(DEBUG) console.log(
'Vad' +
' | sampleRate: ' + this.options.context.sampleRate +
' | hertzPerBin: ' + this.hertzPerBin +
' | iterationFrequency: ' + this.iterationFrequency +
' | iterationPeriod: ' + this.iterationPeriod
);
this.setFilter = function(shape) {
this.filter = [];
for(var i = 0, iLen = this.options.fftSize / 2; i < iLen; i++) {
this.filter[i] = 0;
for(var j = 0, jLen = shape.length; j < jLen; j++) {
if(i * this.hertzPerBin < shape[j].f) {
this.filter[i] = shape[j].v;
break; // Exit j loop
}
}
}
}
this.setFilter(this.options.filter);
this.ready = {};
this.vadState = false; // True when Voice Activity Detected
// Energy detector props
this.energy_offset = this.options.energy_offset;
this.energy_threshold_pos = this.energy_offset * this.options.energy_threshold_ratio_pos;
this.energy_threshold_neg = this.energy_offset * this.options.energy_threshold_ratio_neg;
this.voiceTrend = 0;
this.voiceTrendMax = 10;
this.voiceTrendMin = -10;
this.voiceTrendStart = 5;
this.voiceTrendEnd = -5;
// Create analyser
this.analyser = this.options.context.createAnalyser();
this.analyser.smoothingTimeConstant = this.options.smoothingTimeConstant; // 0.99;
this.analyser.fftSize = this.options.fftSize;
this.floatFrequencyData = new Float32Array(this.analyser.frequencyBinCount);
// Setup local storage of the Linear FFT data
this.floatFrequencyDataLinear = new Float32Array(this.floatFrequencyData.length);
// Connect this.analyser
this.options.source.connect(this.analyser);
// Create ScriptProcessorNode
this.scriptProcessorNode = this.options.context.createScriptProcessor(this.options.bufferLen, 1, 1);
// Connect scriptProcessorNode (Theretically, not required)
this.scriptProcessorNode.connect(this.options.context.destination);
// Create callback to update/analyze floatFrequencyData
var self = this;
this.scriptProcessorNode.onaudioprocess = function(event) {
self.analyser.getFloatFrequencyData(self.floatFrequencyData);
self.update();
self.monitor();
};
// Connect scriptProcessorNode
this.options.source.connect(this.scriptProcessorNode);
// log stuff
this.logging = false;
this.log_i = 0;
this.log_limit = 100;
this.triggerLog = function(limit) {
this.logging = true;
this.log_i = 0;
this.log_limit = typeof limit === 'number' ? limit : this.log_limit;
}
this.log = function(msg) {
if(this.logging && this.log_i < this.log_limit) {
this.log_i++;
console.log(msg);
} else {
this.logging = false;
}
}
this.update = function() {
// Update the local version of the Linear FFT
var fft = this.floatFrequencyData;
for(var i = 0, iLen = fft.length; i < iLen; i++) {
this.floatFrequencyDataLinear[i] = Math.pow(10, fft[i] / 10);
}
this.ready = {};
}
this.getEnergy = function() {
if(this.ready.energy) {
return this.energy;
}
var energy = 0;
var fft = this.floatFrequencyDataLinear;
for(var i = 0, iLen = fft.length; i < iLen; i++) {
energy += this.filter[i] * fft[i] * fft[i];
}
this.energy = energy;
this.ready.energy = true;
return energy;
}
this.monitor = function() {
var energy = this.getEnergy();
var signal = energy - this.energy_offset;
if(signal > this.energy_threshold_pos) {
this.voiceTrend = (this.voiceTrend + 1 > this.voiceTrendMax) ? this.voiceTrendMax : this.voiceTrend + 1;
} else if(signal < -this.energy_threshold_neg) {
this.voiceTrend = (this.voiceTrend - 1 < this.voiceTrendMin) ? this.voiceTrendMin : this.voiceTrend - 1;
} else {
// voiceTrend gets smaller
if(this.voiceTrend > 0) {
this.voiceTrend--;
} else if(this.voiceTrend < 0) {
this.voiceTrend++;
}
}
var start = false, end = false;
if(this.voiceTrend > this.voiceTrendStart) {
// Start of speech detected
start = true;
} else if(this.voiceTrend < this.voiceTrendEnd) {
// End of speech detected
end = true;
}
// Integration brings in the real-time aspect through the relationship with the frequency this functions is called.
var integration = signal * this.iterationPeriod * this.options.energy_integration;
// Idea?: The integration is affected by the voiceTrend magnitude? - Not sure. Not doing atm.
// The !end limits the offset delta boost till after the end is detected.
if(integration > 0 || !end) {
this.energy_offset += integration;
} else {
this.energy_offset += integration * 10;
}
this.energy_offset = this.energy_offset < 0 ? 0 : this.energy_offset;
this.energy_threshold_pos = this.energy_offset * this.options.energy_threshold_ratio_pos;
this.energy_threshold_neg = this.energy_offset * this.options.energy_threshold_ratio_neg;
// Broadcast the messages
if(start && !this.vadState) {
this.vadState = true;
this.options.voice_start();
}
if(end && this.vadState) {
this.vadState = false;
this.options.voice_stop();
}
this.log(
'e: ' + energy +
' | e_of: ' + this.energy_offset +
' | e+_th: ' + this.energy_threshold_pos +
' | e-_th: ' + this.energy_threshold_neg +
' | signal: ' + signal +
' | int: ' + integration +
' | voiceTrend: ' + this.voiceTrend +
' | start: ' + start +
' | end: ' + end
);
return signal;
}
};
window.VAD = VAD;
})(window);
gitextract_z7ivhd_8/
├── LICENSE
├── README.md
├── bower.json
└── lib/
└── vad.js
Condensed preview — 4 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (11K chars).
[
{
"path": "LICENSE",
"chars": 1488,
"preview": "Copyright (c) 2015, Kelly Davis \nAll rights reserved.\n\nRedistribution and use in source and binary forms, with or withou"
},
{
"path": "README.md",
"chars": 1634,
"preview": "# Voice activity detection in Javascript\n\n\n__vad.js__ is a small Javascript library for voice activity detection.\n\n### Q"
},
{
"path": "bower.json",
"chars": 449,
"preview": "{\n \"name\": \"vad.js\",\n \"homepage\": \"https://github.com/kdavis-mozilla/vad.js\",\n \"authors\": [\n \"Kelly Davis <kdavis@"
},
{
"path": "lib/vad.js",
"chars": 7228,
"preview": "(function(window) {\n\n var VAD = function(options) {\n // Default options\n this.options = {\n fftSize: 512,\n "
}
]
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