Feature extraction¶
Spectral features¶
chroma_stft([y, sr, S, norm, n_fft, ...]) | Compute a chromagram from a waveform or power spectrogram. |
chroma_cqt([y, sr, C, hop_length, fmin, ...]) | Constant-Q chromagram |
melspectrogram([y, sr, S, n_fft, hop_length]) | Compute a Mel-scaled power spectrogram. |
mfcc([y, sr, S, n_mfcc]) | Mel-frequency cepstral coefficients |
rmse([y, S, n_fft, hop_length]) | Compute root-mean-square (RMS) energy for each frame. |
spectral_centroid([y, sr, S, n_fft, ...]) | Compute the spectral centroid. |
spectral_bandwidth([y, sr, S, n_fft, ...]) | Compute p’th-order spectral bandwidth: |
spectral_contrast([y, sr, S, n_fft, ...]) | Compute spectral contrast [R11] |
spectral_rolloff([y, sr, S, n_fft, ...]) | Compute roll-off frequency |
poly_features([y, sr, S, n_fft, hop_length, ...]) | Get coefficients of fitting an nth-order polynomial to the columns of a spectrogram. |
tonnetz([y, sr, chroma]) | Computes the tonal centroid features (tonnetz), following the method of [R12]. |
zero_crossing_rate(y[, frame_length, ...]) | Compute the zero-crossing rate of an audio time series. |
Rhythm features¶
tempogram([y, sr, onset_envelope, ...]) | Compute the tempogram: local autocorrelation of the onset strength envelope. |
Feature manipulation¶
delta(data[, width, order, axis, trim]) | Compute delta features: local estimate of the derivative of the input data along the selected axis. |
stack_memory(data[, n_steps, delay]) | Short-term history embedding: vertically concatenate a data vector or matrix with delayed copies of itself. |