WKRD Label & Publishing Co.
Real-Time Sound Feature Laboratory
WKRD Meyda Live Audio Lab
Analyze a microphone, instrument, voice, or uploaded recording while it plays. Watch the waveform, frequency spectrum, pitch-class energy, timbre measurements, loudness indicators, brightness, noisiness, fullness, and sharpness update in real time.
Live feature dashboard
Waiting for an audio source.
Frequency spectrum
Chroma pitch-class energy
Shows the relative presence of C through B. This is useful for harmony visualization, not guaranteed chord detection.
MFCC timbre fingerprint
Thirteen Mel-frequency cepstral coefficients describing the short-term timbre of the sound.
Plain-language live interpretation
These descriptions explain the current short audio frame. They change while the song, voice, or instrument changes.
How to use Meyda measurements correctly
Meyda analyzes small, rapidly changing sections of sound. It is excellent for live meters, music-reactive graphics, instrument demonstrations, voice exercises, education, and timbre comparison. It is not a replacement for the full-song loudness and tempo analysis in the WKRD Essentia Audio Analyzer.
Both rise when the current sound becomes stronger. Compare the same microphone, instrument, distance, and input gain. They are not standardized LUFS measurements.
A higher value usually means a brighter current sound. Cymbals, consonants, distortion, and pick attack can raise it. Compare similar instruments and arrangements.
Values nearer zero indicate a more tonal or peaky spectrum. Values nearer one indicate a flatter, noisier spectrum. Breath, distortion, and percussion can increase it.
Rolloff estimates how far the strong frequency content reaches. Spectral spread describes how broadly frequencies are distributed around the center.
Chroma groups energy into twelve pitch classes. It can reveal harmonic emphasis, but percussion, tuning, overtones, and mixed instruments can make the strongest note misleading.
MFCC values form a timbre description used in speech and sound classification. There is no universal good MFCC shape. Compare repeated takes recorded under matching conditions.