dev-audioprocessing/public/scripts/octave2.js

class OctaveBandProcessor extends AudioWorkletProcessor {
  constructor() {
    super();
    // Define center frequencies for 9 octave bands
    this.centerFrequencies = [63, 125, 250, 500, 1000, 2000, 4000, 8000, 16000];
    this.filters = [];
    this.lastUpdateTimestamp = 0;
    this.updateInterval = 0.125; // Update every 0.125 seconds

    // Create an A-weighting filter for specific frequencies
    this.createAWeightingFilter();

    // Create bandpass filters for each center frequency
    this.centerFrequencies.forEach(frequency => {
      const filter = new BiquadFilterNode(audioContext, {
        type: 'bandpass',
        frequency: frequency,
        Q: 1.41, // Set the desired Q value
      });
      this.filters.push(filter);
    });

    // Set up analyzers for calculating percentiles
    this.setupAnalyzers();
  }

  createAWeightingFilter() {
    // Use the provided A-weighting filter coefficients
    const aWeightingCoefficients = [0, -0.051, -0.142, -0.245, -0.383, -0.65, -1.293, -2.594, -6.554]; //David

    // Create a custom IIR filter node with the A-weighting coefficients
    this.aWeightingFilter = new IIRFilterNode(audioContext, {
      feedforward: aWeightingCoefficients,
      feedback: [1],
    });
  }

  setupAnalyzers() {
    this.analyzers = [];
    this.centerFrequencies.forEach((frequency) => {
      this.analyzers.push([]);
        for (let i = 0; i < 5; i++) { // Unique identifiers from 0 to 4
        const analyzer = audioContext.createAnalyser();
        analyzer.fftSize = 2048;

        // Check if the identifier is 0 (microphone audio) before connecting to the A-weighting filter
        if (i === 0) {
          this.aWeightingFilter.connect(analyzer);
        }

        this.analyzers[this.analyzers.length - 1].push(analyzer);
      }
    })
  }

  process(inputs, outputs) {
    const numOutputChannels = outputs.length;
    for (let i = 0; i < numOutputChannels; i++) {
      const outputChannel = outputs[i][0];
      const inputChannel = inputs[i][0];

      // Apply the filter to the input channel
      const filteredSignal = this.filters[i].process(inputChannel);

      // Apply A-weighting only to the microphone signal (channel 0)
      if (i === 0) {
        const aWeightedSignal = this.aWeightingFilter.process(filteredSignal);
        outputChannel.set(aWeightedSignal);
      } else {
        // For other channels, pass the signal without A-weighting
        outputChannel.set(filteredSignal);
      }

      // Check if it's time to update percentiles
      const currentTime = this.currentTime;
      if (currentTime - this.lastUpdateTimestamp >= this.updateInterval) {
        this.updatePercentiles(i);
        this.lastUpdateTimestamp = currentTime;
      }
    }

    return true;
  }

  calculateRMSLevel(signal, channelIndex) {
    const data = new Float32Array(signal.length);
    signal.copyFromChannel(data, 0);
    const sum = data.reduce((acc, val) => acc + val * val, 0);
    const rmsLevel = Math.sqrt(sum / data.length);
    const dBLevel = 20 * Math.log10(rmsLevel); // Convert to dB
    return dBLevel;
  }

  updatePercentiles(channelIndex) {
    for (let i = 0; i < this.centerFrequencies.length; i++) {
      const analyzer = this.analyzers[i][channelIndex];
      const levelData = new Float32Array(analyzer.frequencyBinCount);
      analyzer.getFloatFrequencyData(levelData);

      // Calculate percentiles for each octave band and each channel
      const percentile10 = this.calculatePercentile(levelData, 10);
      const percentile90 = this.calculatePercentile(levelData, 90);

      const percentileDiff = percentile10 - percentile90;

      // Store the percentile difference for each channel and each octave band
      // You can use suitable data structures to store these values for future comparisons
    }
  }

  calculatePercentile(data, percentile) {
    const sortedData = data.slice().sort((a, b) => a - b);
    const index = Math.floor((percentile / 100) * sortedData.length);
    return sortedData[index];
  }

  combineAndCalculate() {
    let LAF10_90_total = 0; // Initialize the total LAF10%-90%

    for (let i = 0; i < this.centerFrequencies.length; i++) {
      const micAnalyzer = this.analyzers[i][0]; // Analyzer for microphone audio (identifier 0)
      const audioFile1Analyzer = this.analyzers[i][3]; // Analyzer for audioFile1 (identifier 3)
      const audioFile2Analyzer = this.analyzers[i][4]; // Analyzer for audioFile2 (identifier 4)

      // Calculate percentiles for the microphone audio
      const micPercentile10 = this.calculatePercentile(micAnalyzer, 10);
      const micPercentile90 = this.calculatePercentile(micAnalyzer, 90);

      // Calculate percentiles for audioFile1
      const audioFile1Percentile10 = this.calculatePercentile(audioFile1Analyzer, 10);
      const audioFile1Percentile90 = this.calculatePercentile(audioFile1Analyzer, 90);

      // Calculate percentiles for audioFile2
      const audioFile2Percentile10 = this.calculatePercentile(audioFile2Analyzer, 10);
      const audioFile2Percentile90 = this.calculatePercentile(audioFile2Analyzer, 90);

      // Calculate LAF10%-90% for microphone audio, audioFile1, and audioFile2 separately
      const micLAF10_90 = micPercentile10 - micPercentile90;
      const audioFile1LAF10_90 = audioFile1Percentile10 - audioFile1Percentile90;
      const audioFile2LAF10_90 = audioFile2Percentile10 - audioFile2Percentile90;

      // Calculate combined LAF10%-90% for microphone audio, audioFile1, and audioFile2
      const combinedLAF10_90 = micLAF10_90 + audioFile1LAF10_90 + audioFile2LAF10_90;

      // Add the combined LAF10%-90% to the total
      LAF10_90_total += combinedLAF10_90;
    }

    return LAF10_90_total;
  }
}

registerProcessor('octave', OctaveBandProcessor);