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Live Sound Frequency Detector - Online Audio Analyzer

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Live Sound Frequency Detector Ready
Main Frequency
-- Hz
Waiting for signal
Nearest Note
--
--
Level (dBFS)
-- dB
Signal Status
No Signal
Tap Start to begin
Advanced Settings
Lower = more sensitive. Current: 5
Higher = smoother display. Current: 6
Longer peak trail. Current: 5

Frequently Asked Questions

A Live Sound Frequency Detector is an online tool that uses your device's microphone to capture ambient sound in real time and analyze its frequency components. It displays a live spectrogram (frequency spectrum), identifies the dominant frequency, matches it to the nearest musical note, and shows the sound pressure level in decibels (dBFS). This is useful for musicians tuning instruments, audio engineers checking room acoustics, educators demonstrating sound wave properties, and anyone curious about the sounds around them.

The tool leverages the Web Audio API built into modern browsers. When you grant microphone permission, it captures raw audio samples and routes them through an AnalyserNode, which performs Fast Fourier Transform (FFT) to convert the time-domain waveform into frequency-domain data. The frequency spectrum is rendered on an HTML5 Canvas in real time. For precise pitch detection, an autocorrelation algorithm runs on the time-domain samples to determine the fundamental frequency, which is then mapped to the closest musical note (A4=440Hz standard).

The only permission required is microphone access. Your browser will prompt you to allow or deny microphone usage when you click "Start Listening." No other permissions (camera, location, storage, etc.) are requested. The audio is processed entirely on your device and is never recorded, stored, or transmitted anywhere. If you accidentally denied access, you can reset it in your browser's site settings under "Microphone" permissions.

No. All audio processing happens locally on your device using the Web Audio API. The microphone stream is fed directly into the analyzer — no audio is ever recorded to disk, buffered for upload, or transmitted over the network. This tool operates entirely client-side. You can use it offline once the page has loaded. Your privacy is fully protected.

For clean, sustained tones (like a tuning fork, sine wave, or a sung vowel), the autocorrelation-based pitch detector achieves accuracy within ±1 cent (1/100th of a semitone), which rivals dedicated hardware tuners. For complex or noisy signals (multiple instruments, heavy background noise), accuracy decreases. The frequency spectrum display has a resolution determined by the FFT size (2048 samples), giving approximately 21.5 Hz bins at a 44.1kHz sample rate. Interpolation further refines peak detection.

The detectable frequency range depends on your device's microphone and the audio sample rate (typically 44.1kHz or 48kHz). The theoretical maximum is half the sample rate (Nyquist frequency), so approximately 20Hz to 22kHz. In practice, most built-in microphones roll off below 50-80Hz and above 15-18kHz. The spectrum display uses a logarithmic scale from 20Hz to 20kHz for optimal visual representation across the audible range. The note detector covers C0 (~16.4Hz) to B8 (~7.9kHz).

The tool maps frequencies to the standard 12-tone equal temperament scale (A4 = 440Hz). Each semitone step is a factor of 21/12 (≈1.05946). The note name includes the octave number (e.g., A4 is 440Hz, C5 is ~523.25Hz). The "cents" deviation shows how far the detected pitch is from the ideal note: 0 cents = perfectly in tune, +50 cents = halfway to the next semitone, -50 cents = halfway to the previous semitone. A deviation within ±5 cents is considered very accurate.

Yes! The tool is fully responsive and works on iOS (Safari) and Android (Chrome, Firefox). On mobile, the interface adapts to smaller screens with a touch-friendly layout. Note that iOS requires HTTPS for microphone access. Some mobile browsers may also require a user gesture (tap) before activating the audio context. If the microphone doesn't work, ensure your device isn't in silent mode and that the browser has microphone permission enabled in system settings.

Common issues include: (1) Microphone permission denied — check browser site settings. (2) No sound or very quiet sound — the detector requires a minimum volume; try moving closer to the sound source or increasing sensitivity in Advanced Settings. (3) Too much background noise — the algorithm may struggle to lock onto a single frequency; try a quieter environment. (4) Browser compatibility — use Chrome, Firefox, Edge, or Safari 14+. (5) Non-HTTPS connection — microphone access requires a secure context (HTTPS or localhost).

All modern browsers with Web Audio API support: Google Chrome (v35+), Mozilla Firefox (v25+), Microsoft Edge (v79+), Safari (v14+ on desktop and mobile), Opera (v22+), and Samsung Internet. The tool requires a secure context (HTTPS) for getUserMedia microphone access. Internet Explorer is not supported as it lacks the Web Audio API.

Tips for better accuracy: Use a quiet environment with minimal background noise. Bring the sound source closer to the microphone. For musical instrument tuning, play sustained notes rather than short plucks. Use the Advanced Settings panel to adjust the RMS sensitivity threshold — lower values make the detector more sensitive to quiet sounds but more prone to false triggers. The smoothing slider helps stabilize fluctuating readings. For very low frequencies (below 80Hz), ensure your microphone can capture bass frequencies adequately.

Frequency is a physical measurement — the number of sound wave cycles per second, measured in Hertz (Hz). Pitch is the perceptual correlate — how high or low a sound seems to a listener. While frequency is objective and measurable, pitch is subjective and influenced by factors like loudness, timbre, and the listener's hearing. In this tool, we measure frequency (Hz) and map it to musical pitch notation (note names) for practical use.

The frequency spectrum display shows all frequency components simultaneously, so you can visually identify multiple sound sources (e.g., a chord with several notes will show multiple peaks on the spectrum). However, the note detector reports only the single strongest (dominant) frequency at any given moment. For polyphonic analysis (detecting multiple notes simultaneously), more advanced algorithms like harmonic product spectrum or neural network-based polyphonic pitch detection would be needed — which are beyond the scope of this lightweight online tool.
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