🎧 Microphone Signal Quality Analyzer for JavaScript

A lightweight in-browser tool for evaluating microphone signal quality using the Web Audio API. It is designed to help users prepare optimal audio input for speech-to-text models such as Whisper, VOSK, or DeepSpeech — without requiring control over gain settings.

Install and usage

npm i microphone-quality-evaloution@latest

Persian Version

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🔍 Overview

This tool analyzes real-time microphone input and gives simple advice based on:

• RMS (Root Mean Square) energy of your voice
• SNR (Signal-to-Noise Ratio) in the speech frequency band
• Power of the voice signal and background noise
• User behavior (e.g., speaking too softly or loudly)

The output is a short recommendation message, suitable for everyday users (no technical terms), along with a 1–5 mic quality score.

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How to use?

This is the source of this page

// main.js
import { AudioProcessor } from "./audioProcessor.js";

const processor = new AudioProcessor(2000, 250, 4000, false);

const toggleRecordButton = document.querySelector('#toggleRecord');
const toggleResetButton = document.querySelector('#btnReset');
const toggleResetNoiseButton = document.querySelector('#btnResetNoise');
const statusRMS = document.querySelector('#statusRMS');
const statusSNR = document.querySelector('#statusSNR');
const statusQuality = document.querySelector('#quality');
const statusAdvice = document.querySelector('#adviece');

let recording = false;
const RECORD = 'Record';
const STOP = 'Stop';

// Start/Stop recording
toggleRecordButton.addEventListener("click", async () => {
  recording = !recording;
  if (recording) {
    toggleRecordButton.innerHTML = STOP;
    try {
      await processor.start();
      console.log("Start processing...");
    } catch (err) {
      console.error("An error in start processing: ", err);
      statusRMS.innerHTML = `Error: ${err.message}`;
    }
  } else {
    toggleRecordButton.innerHTML = RECORD;
    statusRMS.innerHTML = "Click on Record button and wait for processing noise...";
    statusSNR.innerHTML = "...";
    processor.stop();
  }
});


toggleResetButton.addEventListener("click", () => {
  processor.resetMeasurements();
  recording = false;
  processor.stop();
  toggleRecordButton.innerHTML = RECORD;
  statusRMS.innerHTML = "Click on Record button and wait...";
  statusSNR.innerHTML = "...";
});

toggleResetNoiseButton.addEventListener("click", () => {
  processor.resetMeasurements();
  console.log("Noise and signals are resets...");
});



processor.addEventListener("update", (event) => {
  const { rmsSignal, rmsNoise, snr, noiseMode, timestamp } = event.detail;
  const {message,micQuality} = generateAudioAdvice(snr, rmsSignal);
  
  if (noiseMode) {
    statusRMS.innerHTML = `Messuring noise<br/>RMS Noise: ${rmsNoise}`;
    statusSNR.innerHTML = `SNR: --`;
  } else {
    statusRMS.innerHTML = `RMS Signal: ${rmsSignal}`;
    statusSNR.innerHTML = `SNR: ${snr} dB`;
    statusAdvice.innerHTML = message;
    statusQuality.innerHTML = `${micQuality}/5`
  }
  console.log("بروزرسانی در", new Date(timestamp).toLocaleTimeString(), event.detail);
});


function generateAudioAdvice(snr, rms) {
  let advice = "";
  let micQuality = 0;

  // Evaluate recording quality based on SNR
  if (snr >= 18) {
    advice += "Audio is excellent, ";
    micQuality = 5;
  } else if (snr >= 15) {
    advice += "Audio is good, ";
    micQuality = 4;
  } else if (snr >= 10) {
    advice += "Audio is acceptable, ";
    micQuality = 3;
  } else if (snr >= 5) {
    advice += "Audio is not ideal. Record in a quieter environment, ";
    micQuality = 2;
  } else {
    advice += "Audio is poor; your speech may not be processed correctly, ";
    micQuality = 1;
  }

  // Check the recorded audio level (RMS)
  console.log("RMS: ", rms);
  
  if (rms > 120) {
    advice += "Sound is too loud and may cause noise.";
    if (micQuality > 1) micQuality--;
  } else if (rms < 6) {
    advice += "Adjust the microphone distance.";
    if (micQuality > 1) micQuality--;
  } else {
    advice += "Mic distance seems appropriate.";
  }

  return { message: advice.trim(), micQuality: micQuality };
}

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🧠 Signal Processing works

The tool uses a chain of Web Audio nodes for analysis:

1. MediaStreamSource — receives live audio input from the microphone.
2. BiquadFilterNode (bandpass) — isolates the frequency range typical of human speech:
   • Frequency range: 250 Hz to 4000 Hz
   • Center frequency: $\frac{(250 + 4000)}{2} = 2125 Hz$
   • Quality factor: $Q = \frac{center frequency}{bandwidth}$
3. AnalyserNode — uses FFT (size 16384) to measure the frequency-domain energy.

Every 2 seconds:

• Computes RMS over the target frequency band

• Estimates power of the voice and background noise

• Calculates SNR (in dB) using:

  $\text{SNR}_{dB} = 10 \cdot \log_{10}\left(\frac{P_{\text{signal}}}{P_{\text{noise}}}\right)$

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✅ What Makes “Good” Audio?

Metric	Good Range	Notes
RMS	~20 to 70	Too low = weak voice; too high = possible clipping
SNR	> 15 dB (ideal 18+)	Lower SNR indicates high noise or weak speech

Users are advised to:

• Speak clearly, at a moderate volume
• Move closer to the mic if needed
• Reduce ambient noise (e.g., fans, traffic)

No gain or hardware control is assumed.

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🗣️ Output Example

The tool displays:

• A brief recommendation message (e.g. “Your voice is too quiet”)
• SNR value and RMS level
• A mic quality score between 1 (poor) and 5 (excellent)

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⚙️ Designed For

• Pre-checking mic setup for speech recognition
• Ensuring recording conditions are within model-friendly bounds
• Real-time use in web-based voice tools

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🚀 Future Improvements

• Adaptive multi-band filters for more precise isolation
• ML-based noise profiling and environment classification
• User-specific calibration (tracking speaking habits over time)

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📎 Dependencies

• Web platform only
• No external JS libraries required
• Fully client-side, secure and lightweight

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🧪 Built for experimentation, prototyping, and real-world speech applications.

With ❤️&☕ by codeagha