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79 lines
2.3 KiB
79 lines
2.3 KiB
document.querySelector('#analyze-pitch button').addEventListener('click', startListening);
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function startListening() {
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navigator.mediaDevices.getUserMedia({ audio: true, video: false })
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.then(stream => {
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const audioContext = new (window.AudioContext || window.webkitAudioContext)();
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const analyser = audioContext.createAnalyser();
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const microphone = audioContext.createMediaStreamSource(stream);
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const scriptProcessor = audioContext.createScriptProcessor(2048, 1, 1);
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analyser.smoothingTimeConstant = 0.3;
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analyser.fftSize = 2048;
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microphone.connect(analyser);
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analyser.connect(scriptProcessor);
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scriptProcessor.connect(audioContext.destination);
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scriptProcessor.onaudioprocess = () => {
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const buffer = new Float32Array(analyser.fftSize);
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analyser.getFloatTimeDomainData(buffer);
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const pitch = autoCorrelate(buffer, audioContext.sampleRate);
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document.querySelector('#analyze-pitch dd').textContent = pitch.toFixed(2);
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};
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})
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.catch(err => {
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console.error('Error accessing microphone: ' + err);
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});
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}
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function autoCorrelate(buffer, sampleRate) {
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const SIZE = buffer.length;
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const MAX_SAMPLES = Math.floor(SIZE / 2);
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const MIN_SAMPLES = 0;
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const GOOD_ENOUGH_CORRELATION = 0.9;
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let bestOffset = -1;
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let bestCorrelation = 0;
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let rms = 0;
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let foundGoodCorrelation = false;
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let correlations = new Array(MAX_SAMPLES);
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for (let i = 0; i < SIZE; i++) {
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const val = buffer[i];
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rms += val * val;
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}
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rms = Math.sqrt(rms / SIZE);
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if (rms < 0.01) // not enough signal
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return -1;
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let lastCorrelation = 1;
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for (let offset = MIN_SAMPLES; offset < MAX_SAMPLES; offset++) {
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let correlation = 0;
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for (let i = 0; i < MAX_SAMPLES; i++) {
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correlation += Math.abs((buffer[i]) - (buffer[i + offset]));
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}
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correlation = 1 - (correlation / MAX_SAMPLES);
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correlations[offset] = correlation;
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if ((correlation > GOOD_ENOUGH_CORRELATION) && (correlation > lastCorrelation)) {
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foundGoodCorrelation = true;
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if (correlation > bestCorrelation) {
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bestCorrelation = correlation;
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bestOffset = offset;
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}
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} else if (foundGoodCorrelation) {
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const shift = (correlations[bestOffset + 1] - correlations[bestOffset - 1]) / correlations[bestOffset];
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return sampleRate / (bestOffset + (8 * shift));
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}
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lastCorrelation = correlation;
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}
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if (bestCorrelation > 0.01) {
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return sampleRate / bestOffset;
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}
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return -1;
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}
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