🎧 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

🔍 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.

🧠 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:

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

✅ 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.

🗣️ 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)

⚙️ 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

🚀 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)

📎 Dependencies

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

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

With ❤️&☕ by codeagha