Core IO and DSP

Audio loading

load(path, *[, sr, mono, offset, duration, ...])	Load an audio file as a floating point time series.
stream(path, *, block_length, frame_length, ...)	Stream audio in fixed-length buffers.
to_mono(y)	Convert an audio signal to mono by averaging samples across channels.
resample(y, *, orig_sr, target_sr[, ...])	Resample a time series from orig_sr to target_sr
get_duration(*[, y, sr, S, n_fft, ...])	Compute the duration (in seconds) of an audio time series, feature matrix, or filename.
get_samplerate(path)	Get the sampling rate for a given file.

Time-domain processing

autocorrelate(y, *[, max_size, axis])	Bounded-lag auto-correlation
lpc(y, *, order[, axis])	Linear Prediction Coefficients via Burg's method
zero_crossings(y, *[, threshold, ...])	Find the zero-crossings of a signal y: indices i such that sign(y[i]) != sign(y[j]).
mu_compress(x, *[, mu, quantize])	mu-law compression
mu_expand(x, *[, mu, quantize])	mu-law expansion

Signal generation

clicks(*[, times, frames, sr, hop_length, ...])	Construct a "click track".
tone(frequency, *[, sr, length, duration, phi])	Construct a pure tone (cosine) signal at a given frequency.
chirp(*, fmin, fmax[, sr, length, duration, ...])	Construct a "chirp" or "sine-sweep" signal.

Spectral representations

stft(y, *[, n_fft, hop_length, win_length, ...])	Short-time Fourier transform (STFT).
istft(stft_matrix, *[, hop_length, ...])	Inverse short-time Fourier transform (ISTFT).
reassigned_spectrogram(y, *[, sr, S, n_fft, ...])	Time-frequency reassigned spectrogram.
cqt(y, *[, sr, hop_length, fmin, n_bins, ...])	Compute the constant-Q transform of an audio signal.
icqt(C, *[, sr, hop_length, fmin, ...])	Compute the inverse constant-Q transform.
hybrid_cqt(y, *[, sr, hop_length, fmin, ...])	Compute the hybrid constant-Q transform of an audio signal.
pseudo_cqt(y, *[, sr, hop_length, fmin, ...])	Compute the pseudo constant-Q transform of an audio signal.
vqt(y, *[, sr, hop_length, fmin, n_bins, ...])	Compute the variable-Q transform of an audio signal.
iirt(y, *[, sr, win_length, hop_length, ...])	Time-frequency representation using IIR filters
fmt(y, *[, t_min, n_fmt, kind, beta, ...])	The fast Mellin transform (FMT)
magphase(D, *[, power])	Separate a complex-valued spectrogram D into its magnitude (S) and phase (P) components, so that D = S * P.

Phase recovery

griffinlim(S, *[, n_iter, hop_length, ...])	Approximate magnitude spectrogram inversion using the "fast" Griffin-Lim algorithm.
griffinlim_cqt(C, *[, n_iter, sr, ...])	Approximate constant-Q magnitude spectrogram inversion using the "fast" Griffin-Lim algorithm.

Harmonics

interp_harmonics(x, *, freqs, harmonics[, ...])	Compute the energy at harmonics of time-frequency representation.
salience(S, *, freqs, harmonics[, weights, ...])	Harmonic salience function.
phase_vocoder(D, *, rate[, hop_length, n_fft])	Phase vocoder.

Magnitude scaling

amplitude_to_db(S, *[, ref, amin, top_db])	Convert an amplitude spectrogram to dB-scaled spectrogram.
db_to_amplitude(S_db, *[, ref])	Convert a dB-scaled spectrogram to an amplitude spectrogram.
power_to_db(S, *[, ref, amin, top_db])	Convert a power spectrogram (amplitude squared) to decibel (dB) units
db_to_power(S_db, *[, ref])	Convert a dB-scale spectrogram to a power spectrogram.
perceptual_weighting(S, frequencies, *[, kind])	Perceptual weighting of a power spectrogram.
frequency_weighting(frequencies, *[, kind])	Compute the weighting of a set of frequencies.
multi_frequency_weighting(frequencies, *[, ...])	Compute multiple weightings of a set of frequencies.
A_weighting(frequencies, *[, min_db])	Compute the A-weighting of a set of frequencies.
B_weighting(frequencies, *[, min_db])	Compute the B-weighting of a set of frequencies.
C_weighting(frequencies, *[, min_db])	Compute the C-weighting of a set of frequencies.
D_weighting(frequencies, *[, min_db])	Compute the D-weighting of a set of frequencies.
pcen(S, *[, sr, hop_length, gain, bias, ...])	Per-channel energy normalization (PCEN)

Time unit conversion

frames_to_samples(frames, *[, hop_length, n_fft])	Converts frame indices to audio sample indices.
frames_to_time(frames, *[, sr, hop_length, ...])	Converts frame counts to time (seconds).
samples_to_frames(samples, *[, hop_length, ...])	Converts sample indices into STFT frames.
samples_to_time(samples, *[, sr])	Convert sample indices to time (in seconds).
time_to_frames(times, *[, sr, hop_length, n_fft])	Converts time stamps into STFT frames.
time_to_samples(times, *[, sr])	Convert timestamps (in seconds) to sample indices.
blocks_to_frames(blocks, *, block_length)	Convert block indices to frame indices
blocks_to_samples(blocks, *, block_length, ...)	Convert block indices to sample indices
blocks_to_time(blocks, *, block_length, ...)	Convert block indices to time (in seconds)

Frequency unit conversion

hz_to_note(frequencies, **kwargs)	Convert one or more frequencies (in Hz) to the nearest note names.
hz_to_midi(frequencies)	Get MIDI note number(s) for given frequencies
hz_to_svara_h(frequencies, *, Sa[, abbr, ...])	Convert frequencies (in Hz) to Hindustani svara
hz_to_svara_c(frequencies, *, Sa, mela[, ...])	Convert frequencies (in Hz) to Carnatic svara
midi_to_hz(notes)	Get the frequency (Hz) of MIDI note(s)
midi_to_note(midi, *[, octave, cents, key, ...])	Convert one or more MIDI numbers to note strings.
midi_to_svara_h(midi, *, Sa[, abbr, octave, ...])	Convert MIDI numbers to Hindustani svara
midi_to_svara_c(midi, *, Sa, mela[, abbr, ...])	Convert MIDI numbers to Carnatic svara within a given melakarta raga
note_to_hz(note, **kwargs)	Convert one or more note names to frequency (Hz)
note_to_midi(note, *[, round_midi])	Convert one or more spelled notes to MIDI number(s).
note_to_svara_h(notes, *, Sa[, abbr, ...])	Convert western notes to Hindustani svara
note_to_svara_c(notes, *, Sa, mela[, abbr, ...])	Convert western notes to Carnatic svara
hz_to_mel(frequencies, *[, htk])	Convert Hz to Mels
hz_to_octs(frequencies, *[, tuning, ...])	Convert frequencies (Hz) to (fractional) octave numbers.
mel_to_hz(mels, *[, htk])	Convert mel bin numbers to frequencies
octs_to_hz(octs, *[, tuning, bins_per_octave])	Convert octaves numbers to frequencies.
A4_to_tuning(A4, *[, bins_per_octave])	Convert a reference pitch frequency (e.g., A4=435) to a tuning estimation, in fractions of a bin per octave.
tuning_to_A4(tuning, *[, bins_per_octave])	Convert a tuning deviation (from 0) in fractions of a bin per octave (e.g., tuning=-0.1) to a reference pitch frequency relative to A440.

Music notation

key_to_notes(key, *[, unicode])	Lists all 12 note names in the chromatic scale, as spelled according to a given key (major or minor).
key_to_degrees(key)	Construct the diatonic scale degrees for a given key.
mela_to_svara(mela, *[, abbr, unicode])	Spell the Carnatic svara names for a given melakarta raga
mela_to_degrees(mela)	Construct the svara indices (degrees) for a given melakarta raga
thaat_to_degrees(thaat)	Construct the svara indices (degrees) for a given thaat
list_mela()	List melakarta ragas by name and index.
list_thaat()	List supported thaats by name.

Frequency range generation

fft_frequencies(*[, sr, n_fft])	Alternative implementation of np.fft.fftfreq
cqt_frequencies(n_bins, *, fmin[, ...])	Compute the center frequencies of Constant-Q bins.
mel_frequencies([n_mels, fmin, fmax, htk])	Compute an array of acoustic frequencies tuned to the mel scale.
tempo_frequencies(n_bins, *[, hop_length, sr])	Compute the frequencies (in beats per minute) corresponding to an onset auto-correlation or tempogram matrix.
fourier_tempo_frequencies(*[, sr, ...])	Compute the frequencies (in beats per minute) corresponding to a Fourier tempogram matrix.

Pitch and tuning

pyin(y, *, fmin, fmax[, sr, frame_length, ...])	Fundamental frequency (F0) estimation using probabilistic YIN (pYIN).
yin(y, *, fmin, fmax[, sr, frame_length, ...])	Fundamental frequency (F0) estimation using the YIN algorithm.
estimate_tuning(*[, y, sr, S, n_fft, ...])	Estimate the tuning of an audio time series or spectrogram input.
pitch_tuning(frequencies, *[, resolution, ...])	Given a collection of pitches, estimate its tuning offset (in fractions of a bin) relative to A440=440.0Hz.
piptrack(*[, y, sr, S, n_fft, hop_length, ...])	Pitch tracking on thresholded parabolically-interpolated STFT.

Miscellaneous

samples_like(X, *[, hop_length, n_fft, axis])	Return an array of sample indices to match the time axis from a feature matrix.
times_like(X, *[, sr, hop_length, n_fft, axis])	Return an array of time values to match the time axis from a feature matrix.
get_fftlib()	Get the FFT library currently used by librosa
set_fftlib([lib])	Set the FFT library used by librosa.