Test mit octave.js
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class OctaveBandProcessor extends AudioWorkletProcessor {
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constructor() {
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super();
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// Define center frequencies for 9 octave bands
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this.centerFrequencies = [63, 125, 250, 500, 1000, 2000, 4000, 8000, 16000];
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this.filters = [];
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this.lastUpdateTimestamp = 0;
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this.updateInterval = 0.125; // Update every 0.125 seconds
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constructor() {
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super()
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// Define center frequencies for 9 octave bands
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this.centerFrequencies = [63, 125, 250, 500, 1000, 2000, 4000, 8000, 16000]
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this.filters = []
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this.lastUpdateTimestamp = 0
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this.updateInterval = 0.125 // Update every 0.125 seconds
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// Create an A-weighting filter for specific frequencies
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this.createAWeightingFilter();
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// Create an A-weighting filter for specific frequencies
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this.createAWeightingFilter()
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// Create bandpass filters for each center frequency
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this.centerFrequencies.forEach(frequency => {
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const filter = new BiquadFilterNode(audioContext, {
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type: 'bandpass',
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frequency: frequency,
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Q: 1.41, // Set the desired Q value
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},
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this.filters.push(filter))
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});
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// Create bandpass filters for each center frequency
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this.centerFrequencies.forEach((frequency) => {
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const filter = new BiquadFilterNode(
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audioContext,
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{
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type: "bandpass",
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frequency: frequency,
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Q: 1.41, // Set the desired Q value
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},
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this.filters.push(filter),
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)
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})
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// Set up analyzers for calculating percentiles
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this.setupAnalyzers();
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// Set up analyzers for calculating percentiles
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this.setupAnalyzers()
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}
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}
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setupAnalyzers() {
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this.analyzers = []
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this.centerFrequencies.forEach((frequency) => {
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this.analyzers.push([])
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for (let i = 0; i < 5; i++) {
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// Unique identifiers from 0 to 4
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const analyzer = audioContext.createAnalyser()
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analyzer.fftSize = 2048
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setupAnalyzers() {
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this.analyzers = [];
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this.centerFrequencies.forEach(frequency => {
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this.analyzers.push([]);
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for (let i = 0; i < 5; i++) { // Unique identifiers from 0 to 4
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const analyzer = audioContext.createAnalyser();
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analyzer.fftSize = 2048;
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// Check if the identifier is 0 (microphone audio) before connecting to the A-weighting filter
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if (i === 0) {
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this.aWeightingFilter.connect(analyzer)
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}
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// Check if the identifier is 0 (microphone audio) before connecting to the A-weighting filter
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if (i === 0) {
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this.aWeightingFilter.connect(analyzer);
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}
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this.analyzers[this.analyzers.length - 1].push(analyzer)
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}
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})
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}
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this.analyzers[this.analyzers.length - 1].push(analyzer);
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}
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})
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}
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process(inputs, outputs) {
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const numOutputChannels = outputs.length
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for (let i = 0; i < numOutputChannels; i++) {
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const outputChannel = outputs[i][0]
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const inputChannel = inputs[i][0]
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process(inputs, outputs) {
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const numOutputChannels = outputs.length;
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for (let i = 0; i < numOutputChannels; i++) {
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const outputChannel = outputs[i][0];
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const inputChannel = inputs[i][0];
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// Apply the filter to the input channel
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const filteredSignal = this.filters[i].process(inputChannel)
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// Apply the filter to the input channel
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const filteredSignal = this.filters[i].process(inputChannel);
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// Apply A-weighting only to the microphone signal (channel 0)
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if (i === 0) {
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const aWeightedSignal = this.aWeightingFilter.process(filteredSignal)
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outputChannel.set(aWeightedSignal)
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} else {
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// For other channels, pass the signal without A-weighting
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outputChannel.set(filteredSignal)
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}
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// Apply A-weighting only to the microphone signal (channel 0)
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if (i === 0) {
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const aWeightedSignal = this.aWeightingFilter.process(filteredSignal);
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outputChannel.set(aWeightedSignal);
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} else {
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// For other channels, pass the signal without A-weighting
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outputChannel.set(filteredSignal);
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}
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// Check if it's time to update percentiles
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const currentTime = this.currentTime
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if (currentTime - this.lastUpdateTimestamp >= this.updateInterval) {
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this.updatePercentiles(i)
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this.lastUpdateTimestamp = currentTime
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}
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}
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// Check if it's time to update percentiles
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const currentTime = this.currentTime;
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if (currentTime - this.lastUpdateTimestamp >= this.updateInterval) {
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this.updatePercentiles(i);
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this.lastUpdateTimestamp = currentTime;
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}
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}
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return true
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}
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return true;
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}
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calculateRMSLevel(signal, channelIndex) {
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const data = new Float32Array(signal.length)
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signal.copyFromChannel(data, 0)
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const sum = data.reduce((acc, val) => acc + val * val, 0)
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const rmsLevel = Math.sqrt(sum / data.length)
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const dBLevel = 20 * Math.log10(rmsLevel) // Convert to dB
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return dBLevel
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}
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calculateRMSLevel(signal, channelIndex) {
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const data = new Float32Array(signal.length);
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signal.copyFromChannel(data, 0);
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const sum = data.reduce((acc, val) => acc + val * val, 0);
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const rmsLevel = Math.sqrt(sum / data.length);
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const dBLevel = 20 * Math.log10(rmsLevel); // Convert to dB
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return dBLevel;
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}
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updatePercentiles(channelIndex) {
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for (let i = 0; i < this.centerFrequencies.length; i++) {
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const analyzer = this.analyzers[i][channelIndex]
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const levelData = new Float32Array(analyzer.frequencyBinCount)
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analyzer.getFloatFrequencyData(levelData)
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updatePercentiles(channelIndex) {
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for (let i = 0; i < this.centerFrequencies.length; i++) {
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const analyzer = this.analyzers[i][channelIndex];
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const levelData = new Float32Array(analyzer.frequencyBinCount);
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analyzer.getFloatFrequencyData(levelData);
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// Calculate percentiles for each octave band and each channel
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const percentile10 = this.calculatePercentile(levelData, 10)
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const percentile90 = this.calculatePercentile(levelData, 90)
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// Calculate percentiles for each octave band and each channel
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const percentile10 = this.calculatePercentile(levelData, 10);
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const percentile90 = this.calculatePercentile(levelData, 90);
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const percentileDiff = percentile10 - percentile90
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const percentileDiff = percentile10 - percentile90;
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// Store the percentile difference for each channel and each octave band
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// You can use suitable data structures to store these values for future comparisons
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}
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}
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// Store the percentile difference for each channel and each octave band
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// You can use suitable data structures to store these values for future comparisons
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}
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}
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calculatePercentile(data, percentile) {
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const sortedData = data.slice().sort((a, b) => a - b)
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const index = Math.floor((percentile / 100) * sortedData.length)
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return sortedData[index]
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}
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calculatePercentile(data, percentile) {
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const sortedData = data.slice().sort((a, b) => a - b);
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const index = Math.floor((percentile / 100) * sortedData.length);
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return sortedData[index];
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}
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createAWeightingFilter() {
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// Use the provided A-weighting filter coefficients
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const aWeightingCoefficients = [
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0, -0.051, -0.142, -0.245, -0.383, -0.65, -1.293, -2.594, -6.554,
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] //David
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createAWeightingFilter() {
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// Use the provided A-weighting filter coefficients
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const aWeightingCoefficients = [0, -0.051, -0.142, -0.245, -0.383, -0.65, -1.293, -2.594, -6.554]; //David
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// Create a custom IIR filter node with the A-weighting coefficients
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this.aWeightingFilter = new IIRFilterNode(audioContext, {
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feedforward: aWeightingCoefficients,
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feedback: [1],
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})
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}
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// Create a custom IIR filter node with the A-weighting coefficients
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this.aWeightingFilter = new IIRFilterNode(audioContext, {
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feedforward: aWeightingCoefficients,
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feedback: [1],
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});
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}
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combineAndCalculate() {
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let LAF10_90_total = 0 // Initialize the total LAF10%-90%
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for (let i = 0; i < this.centerFrequencies.length; i++) {
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const micAnalyzer = this.analyzers[i][0] // Analyzer for microphone audio (identifier 0)
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const audioFile1Analyzer = this.analyzers[i][3] // Analyzer for audioFile1 (identifier 3)
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const audioFile2Analyzer = this.analyzers[i][4] // Analyzer for audioFile2 (identifier 4)
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// Calculate percentiles for the microphone audio
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const micPercentile10 = this.calculatePercentile(micAnalyzer, 10)
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const micPercentile90 = this.calculatePercentile(micAnalyzer, 90)
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combineAndCalculate() {
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let LAF10_90_total = 0; // Initialize the total LAF10%-90%
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// Calculate percentiles for audioFile1
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const audioFile1Percentile10 = this.calculatePercentile(
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audioFile1Analyzer,
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10,
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)
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const audioFile1Percentile90 = this.calculatePercentile(
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audioFile1Analyzer,
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90,
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)
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for (let i = 0; i < this.centerFrequencies.length; i++) {
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const micAnalyzer = this.analyzers[i][0]; // Analyzer for microphone audio (identifier 0)
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const audioFile1Analyzer = this.analyzers[i][3]; // Analyzer for audioFile1 (identifier 3)
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const audioFile2Analyzer = this.analyzers[i][4]; // Analyzer for audioFile2 (identifier 4)
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// Calculate percentiles for audioFile2
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const audioFile2Percentile10 = this.calculatePercentile(
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audioFile2Analyzer,
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10,
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)
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const audioFile2Percentile90 = this.calculatePercentile(
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audioFile2Analyzer,
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90,
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)
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// Calculate percentiles for the microphone audio
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const micPercentile10 = this.calculatePercentile(micAnalyzer, 10);
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const micPercentile90 = this.calculatePercentile(micAnalyzer, 90);
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// Calculate LAF10%-90% for microphone audio, audioFile1, and audioFile2 separately
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const micLAF10_90 = micPercentile10 - micPercentile90
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const audioFile1LAF10_90 = audioFile1Percentile10 - audioFile1Percentile90
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const audioFile2LAF10_90 = audioFile2Percentile10 - audioFile2Percentile90
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// Calculate percentiles for audioFile1
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const audioFile1Percentile10 = this.calculatePercentile(audioFile1Analyzer, 10);
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const audioFile1Percentile90 = this.calculatePercentile(audioFile1Analyzer, 90);
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// Calculate combined LAF10%-90% for microphone audio, audioFile1, and audioFile2
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const combinedLAF10_90 =
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micLAF10_90 + audioFile1LAF10_90 + audioFile2LAF10_90
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// Calculate percentiles for audioFile2
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const audioFile2Percentile10 = this.calculatePercentile(audioFile2Analyzer, 10);
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const audioFile2Percentile90 = this.calculatePercentile(audioFile2Analyzer, 90);
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// Calculate LAF10%-90% for microphone audio, audioFile1, and audioFile2 separately
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const micLAF10_90 = micPercentile10 - micPercentile90;
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const audioFile1LAF10_90 = audioFile1Percentile10 - audioFile1Percentile90;
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const audioFile2LAF10_90 = audioFile2Percentile10 - audioFile2Percentile90;
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// Calculate combined LAF10%-90% for microphone audio, audioFile1, and audioFile2
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const combinedLAF10_90 = micLAF10_90 + audioFile1LAF10_90 + audioFile2LAF10_90;
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// Add the combined LAF10%-90% to the total
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LAF10_90_total += combinedLAF10_90;
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}
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// return LAF10_90_total;
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}
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// Add the combined LAF10%-90% to the total
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LAF10_90_total += combinedLAF10_90
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}
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// return LAF10_90_total;
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}
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}
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registerProcessor('octave', OctaveBandProcessor);
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registerProcessor("octave", OctaveBandProcessor)
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