`athena.transform.feats.mfcc`¶

This model extracts MFCC features per frame.

Module Contents¶

Classes¶

Mfcc

Compute MFCC features of every frame in speech.

class athena.transform.feats.mfcc.Mfcc(config: dict)¶

Bases: athena.transform.feats.base_frontend.BaseFrontend

Compute MFCC features of every frame in speech.

Parameters: config – contains fifteen optional parameters.

Shape:

output: \((C, T, F)\).

Examples::

>>> config = {'cepstral_lifter': 22.0, 'coefficient_count': 13}
>>> mfcc_op = Mfcc.params(config).instantiate()
>>> mfcc_out = mfcc_op('test.wav', 16000)

classmethod params(config=None)¶

Set params.

Parameters

config – contains the following fifteen optional parameters:
'window_length' – Window length in seconds. (float, default = 0.025),
'frame_length' – Hop length in seconds. (float, default = 0.010),
'snip_edges' – If 1, the last frame (shorter than window_length) will be cutoff. If 2, 1 // 2 frame_length data will be padded to data. (int, default = 1),
'preEph_coeff' – Coefficient for use in frame-signal preemphasis. (float, default = 0.97),
'window_type' – Type of window (“hamm”|”hann”|”povey”|”rect”|”blac”|”tria”). (string, default = “povey”)
'remove_dc_offset' – Subtract mean from waveform on each frame. (bool, default = true)
'is_fbank' – If true, compute power spetrum without frame energy. If false, using the frame energy instead of the square of the constant component of the signal. (bool, default = true)
'coefficient_count' – Number of cepstra in MFCC computation. (int, default = 13)
'output_type' – If 1, return power spectrum. If 2, return log-power spectrum. (int, default = 1)
'upper_frequency_limit' – High cutoff frequency for mel bins (if <= 0, offset from Nyquist) (float, default = 0)
'lower_frequency_limit' – Low cutoff frequency for mel bins. (float, default = 20)
'filterbank_channel_count' – Number of triangular mel-frequency bins. (float, default = 23)
'dither' – Dithering constant (0.0 means no dither). (float, default = 1) [add robust to training]
'cepstral_lifter' – Constant that controls scaling of MFCCs. (float, default = 22)
'use_energy' – Use energy (not C0) in MFCC computation. (bool, default = True)

Note

Return an object of class HParams, which is a set of hyperparameters as name-value pairs.

call(audio_data, sample_rate)¶

Caculate mfcc features of audio data.