Why does my voice show multiple lines in the spectrum, not just one?

The human voice is a complex sound. Your vocal cords produce a fundamental frequency (the pitch you hear), but your vocal tract resonates, amplifying specific integer multiples called harmonics or overtones. The spectrum shows this full set of frequencies. The unique blend of these harmonics is what gives your voice its distinctive timbre, different from a tuning fork's pure tone.

What does the height of the bars in the frequency graph represent?

The height (magnitude) represents the relative strength or loudness of each frequency component present in the sound. A taller bar means that particular sinusoidal frequency is a more dominant part of the overall sound. For a pure tone, only one bar is high. For a noisy sound like clapping, many bars across a wide range will be similarly high.

Why does the waveform sometimes look messy even when I hear a steady note?

A steady musical note is still a complex wave. The waveform you see is the sum of the fundamental frequency and all its harmonics. This superposition creates a repeating but non-sinusoidal pattern. The 'messiness' is the structure of that specific timbre. If you whistle a pure tone, the waveform will appear as a clean, repeating sine wave.

Can this simulator measure the exact loudness in decibels?

Not directly. The amplitude axis is typically in arbitrary relative units. To measure sound pressure level in decibels (dB), the simulator would need calibration with a known reference pressure. It shows relative amplitude changes well: speaking louder makes the waveform taller and the spectrum bars higher, which correlates correctly with an increase in dB.

Sound Wave Visualizer

Real-time waveform and frequency spectrum from microphone.

About this model

Sound is a longitudinal pressure wave that propagates through a medium like air. This visualizer captures real-time audio input from a microphone and translates it into two fundamental representations. The first is a waveform plot, showing air pressure variation (amplitude) against time. This graph directly illustrates the principle of superposition, where complex sounds are the sum of simpler sine waves. The second is a frequency spectrum, generated by applying a Fast Fourier Transform (FFT) algorithm to the time-domain signal. The FFT decomposes the complex waveform into its constituent sinusoidal frequencies, plotting the magnitude of each frequency component. This demonstrates Fourier's theorem and allows users to see the harmonic content of a sound. The simulator models core acoustic concepts: frequency (pitch, measured in Hertz), amplitude (loudness, related to sound pressure level), and timbre (the unique quality of a sound determined by its harmonic spectrum). Key simplifications include analyzing the signal in a short time window, which provides a 'snapshot' spectrum, and not modeling the propagation of sound through space or complex phenomena like resonance in rooms. By interacting with it, students learn to connect the physical sensation of sound with its mathematical representation, observe how pure tones produce a single spectral peak while complex sounds (like voice or music) show a broad distribution, and verify the inverse relationship between period and frequency in the waveform view.

Who it's for: High school and introductory undergraduate physics students studying waves, sound, and signal processing, as well as music technology and acoustics enthusiasts.

Key terms

Waveform
Frequency Spectrum
Fast Fourier Transform (FFT)
Amplitude
Frequency (Hz)
Pitch
Timbre
Sound Pressure

How it works

Live waveform (pressure vs time) and a bar spectrum from your microphone using the Web Audio API. Speak, clap, or play music — peaks in the spectrum show which frequencies carry energy.

Key equations

Bin i ≈ i · (sampleRate / FFT size) Hz up to Nyquist f_N = sampleRate / 2

Frequently asked questions

Why does my voice show multiple lines in the spectrum, not just one?: The human voice is a complex sound. Your vocal cords produce a fundamental frequency (the pitch you hear), but your vocal tract resonates, amplifying specific integer multiples called harmonics or overtones. The spectrum shows this full set of frequencies. The unique blend of these harmonics is what gives your voice its distinctive timbre, different from a tuning fork's pure tone.
What does the height of the bars in the frequency graph represent?: The height (magnitude) represents the relative strength or loudness of each frequency component present in the sound. A taller bar means that particular sinusoidal frequency is a more dominant part of the overall sound. For a pure tone, only one bar is high. For a noisy sound like clapping, many bars across a wide range will be similarly high.
Why does the waveform sometimes look messy even when I hear a steady note?: A steady musical note is still a complex wave. The waveform you see is the sum of the fundamental frequency and all its harmonics. This superposition creates a repeating but non-sinusoidal pattern. The 'messiness' is the structure of that specific timbre. If you whistle a pure tone, the waveform will appear as a clean, repeating sine wave.
Can this simulator measure the exact loudness in decibels?: Not directly. The amplitude axis is typically in arbitrary relative units. To measure sound pressure level in decibels (dB), the simulator would need calibration with a known reference pressure. It shows relative amplitude changes well: speaking louder makes the waveform taller and the spectrum bars higher, which correlates correctly with an increase in dB.

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Sound Wave Visualizer

About this model

How it works

Key equations

Frequently asked questions

Related simulators

Doppler Effect

Transverse vs Longitudinal

Wave on a String

Acoustic Levitation (Schematic)

Beat Frequency

Resonance Tube

Sound Wave Visualizer

About this model

How it works

Key equations

Frequently asked questions