Multi-Tone Frequency Detector

This multi-tone frequency detector reveals all simultaneous frequencies in any sound — not just the dominant one. Decode DTMF keypad tones, identify chords by name, display musical intervals between detected tones, and visualize results on a live spectrogram with peak markers. All processing runs locally in your browser.

🔒 Your audio never leaves your device — 100% local processing, zero uploads. Chrome Firefox Safari Edge

Upload Audio

Space Start/Stop R Reset C Calibrate F Freeze

Microphone:

Sensitivity -50 dB

Mode General

Active Tones

Detected Tones

Start listening to detect frequencies

DTMF Decoded Output

Decoded: —

Chord Identification

—

Waiting for tones...

Musical Intervals

Detect two or more tones to see intervals

Frequency Spectrum LOG

Spectrogram (time vs frequency)

History Log

Time	Tones	Notes	DTMF	Chord

How to Use the Multi-Tone Frequency Detector

Start Listening or Upload Audio

Click "Start Listening" and grant microphone permission, or use "Upload Audio" to analyze a recorded file. Select your preferred input device from the microphone dropdown.
Adjust Sensitivity and Mode

Use the sensitivity slider to control the detection threshold. Switch between General mode (all frequencies) and DTMF mode (optimized for detecting telephone keypad dual-tone pairs).
Review Detected Tones

The Detected Tones panel shows every frequency above the threshold with its Hz value, dB level, and nearest musical note. Each tone has its own level bar for quick visual comparison.
Check DTMF, Chord, and Intervals

In DTMF mode, decoded keypad characters appear in real time. The Chord Identification card names the chord formed by the detected notes. The Musical Intervals section shows the interval between each pair of tones.
Export or Copy Results

Use "Copy All Results" for clipboard access, or "Export CSV" to download your full session history for documentation and further analysis.

Understanding Your Results

Detected Tones

Unlike a single-frequency detector, this tool identifies all simultaneous frequency components above the threshold. Each tone is displayed with its frequency in Hz, amplitude in dB, and the closest musical note name. This is essential for analyzing complex signals that contain multiple overlapping tones, from guitar chords and piano voicings to telephony signals and industrial noise. For generating known multi-tone test signals to feed into this detector, try the multi-frequency mixer.

DTMF Decoding

DTMF (Dual-Tone Multi-Frequency) signaling encodes keypad digits as pairs of frequencies. When two tones match a valid row/column pair (e.g., 697 Hz + 1209 Hz = digit "1"), the decoder maps them to the corresponding key. The decoded string accumulates over time, showing the full dialed sequence. This is useful for verifying telephone equipment, decoding recorded IVR dial tones, and testing VoIP systems where DTMF sometimes fails to transmit reliably over compressed audio codecs.

Chord Identification

The built-in chord analyzer compares the detected musical notes against a database of common chord voicings including major, minor, diminished, augmented, seventh, and suspended chords. The chord card displays the root note, chord quality, and the constituent notes. Note that chord inversion (where the bass note is not the root) is handled by testing every detected note as a potential root, so first-inversion and second-inversion voicings are still recognized when the right pitch classes are present.

Musical Intervals

For every pair of detected tones, the interval is calculated in semitones and named using standard musical terminology (unison, minor 2nd, major 3rd, perfect 5th, octave, etc.). This helps musicians identify harmonic relationships between frequencies and is particularly useful for ear training, verifying tuning accuracy, and analyzing the consonance or dissonance of a sound.

Spectrogram

The spectrogram shows frequency vs. time as a scrolling color map. Brighter colors indicate higher amplitude. Peak markers highlight the strongest detected tones. This visualization reveals how the frequency content of a sound evolves over time, making it easy to spot transients, sustained tones, vibrato, and formant structure in voice or instruments. For a higher-resolution static snapshot of the frequency spectrum, the FFT frequency analyzer offers more spectral detail.

Tone Count

The active tone count shows how many distinct frequencies are currently detected above the threshold. This provides a quick overview of signal complexity and helps diagnose whether the sensitivity slider is set too high (counting noise peaks as tones) or too low (missing quiet partials).

How Multi-Tone Detection Works

FFT Multi-Peak Detection

The core of multi-tone detection is the Fast Fourier Transform (FFT), which converts time-domain audio samples into a frequency spectrum. Unlike single-peak detectors that find only the loudest bin, this tool scans the entire spectrum for all local maxima above the sensitivity threshold. Each candidate peak must exceed its immediate neighbors and maintain a minimum frequency separation (typically 40–80 Hz) to avoid counting spectral leakage artifacts as separate tones. Parabolic interpolation on the three bins surrounding each peak refines the frequency estimate to sub-bin accuracy. The result is a list of discrete frequency components, each with an interpolated Hz value and an amplitude in dB, representing every distinct tone present in the signal.

DTMF Frequency Pairs

The DTMF standard encodes 16 symbols (0–9, *, #, A–D) using pairs of sinusoidal tones. One tone comes from a low-frequency row group (697, 770, 852, or 941 Hz) and the other from a high-frequency column group (1209, 1336, 1477, or 1633 Hz). When the detector finds exactly one peak within ±2% of a row frequency and one peak within ±2% of a column frequency, it maps the pair to the corresponding keypad symbol. The dual-tone design ensures that no single voice frequency can accidentally trigger a digit, making DTMF robust for telephony signaling over analog lines.

Chord Database and Matching

Chord identification begins by mapping each detected frequency to its nearest pitch class (C, C#, D, ... B) using the formula 12 * log2(hz / 440) + 69 to convert Hz to a MIDI note number, then reducing modulo 12. The resulting set of pitch classes is compared against a chord database containing common voicings: major triads (0-4-7 semitones), minor triads (0-3-7), diminished (0-3-6), augmented (0-4-8), dominant 7th (0-4-7-10), major 7th (0-4-7-11), minor 7th (0-3-7-10), and suspended chords (sus2: 0-2-7, sus4: 0-5-7). The algorithm tests every detected note as a potential root and checks whether the remaining intervals match any known pattern. When a match is found, the chord name and quality are displayed instantly.

Frequently Asked Questions

How many simultaneous tones can this tool detect?

The detector can identify up to 20 simultaneous frequency peaks above the sensitivity threshold. In practice, most real-world signals contain 2–8 significant tones. The number of detectable peaks depends on the FFT size, sensitivity setting, and how well-separated the frequencies are.

What is DTMF and when would I use the DTMF mode?

DTMF (Dual-Tone Multi-Frequency) is the signaling system used by telephone keypads. Each key press generates two simultaneous tones. Use DTMF mode to decode recorded phone dial tones, test telephone equipment, or verify DTMF generators. The mode optimizes detection sensitivity for the specific DTMF frequency ranges.

How accurate is the chord identification?

Chord identification is most accurate with clean, sustained tones such as keyboard or guitar chords played individually. The algorithm matches detected pitch classes against a database of common chord types. Complex or heavily distorted signals may produce false identifications. The tool supports major, minor, diminished, augmented, 7th, major 7th, minor 7th, sus2, and sus4 chord types.

What is the difference between this and a single frequency detector?

A single frequency detector finds only the one loudest frequency in the audio signal. This multi-tone detector finds all significant frequencies simultaneously, making it essential for analyzing chords, DTMF signals, harmonic content, or any sound with multiple overlapping tones.

Can I analyze audio files instead of using a microphone?

Yes. Click "Upload Audio" to load any audio file (WAV, MP3, OGG, FLAC, etc.) from your device. The file is decoded and analyzed locally — nothing is uploaded to a server. This is useful for analyzing recordings of DTMF sequences, musical content, or noise samples.

What do the musical intervals mean?

Musical intervals describe the pitch distance between two notes. They are measured in semitones (half steps) and named using standard terminology: unison (0), minor 2nd (1), major 2nd (2), minor 3rd (3), major 3rd (4), perfect 4th (5), tritone (6), perfect 5th (7), and so on up to the octave (12).

Is my audio data private?

Absolutely. All frequency detection and analysis runs 100% in your browser using the Web Audio API. No audio data is ever recorded, transmitted, or stored on any server. The tool works completely offline once loaded.

Why does the tool detect extra tones I didn't play?

Extra detected frequencies are usually harmonics or spectral leakage. Real instruments produce overtones at integer multiples of the fundamental, so a single guitar note can appear as several peaks. Room acoustics, microphone resonances, and slight sensitivity-threshold settings that are too low can also let noise floor peaks register as tones. Try raising the sensitivity slider (toward −30 dB) until spurious peaks disappear while genuine tones remain.

Can I use this to transcribe music by ear — detect all notes in a chord played on an instrument?

Yes, with caveats. Clean, sustained chords on instruments like piano or synthesizer work well because each note produces a clear fundamental peak. However, instruments with strong harmonics (electric guitar with distortion, violin, brass) can produce so many overtone peaks that chord identification becomes unreliable. For best results use the General mode, pluck or play chords cleanly and let them sustain, then check the Chord Identification card while the chord is ringing.

Does the tool work with uploaded audio files, and what formats are supported?

Yes — click "Upload Audio" to analyze a file stored on your device. Supported formats depend on your browser's built-in audio decoder, but all modern browsers accept WAV, MP3, OGG, and FLAC; most also accept AAC and WebM. The file is decoded locally at full quality; nothing is uploaded. This is particularly useful for analyzing DTMF sequences captured in call recordings or for studying the harmonic content of archived audio samples.

🎙