athena.transform.feats.add_rir_noise_aecres

This model adds noise/rir to signal.

Module Contents

Classes

Add_rir_noise_aecres

Add a random signal-to-noise ratio noise or impulse response to clean speech.

class athena.transform.feats.add_rir_noise_aecres.Add_rir_noise_aecres(config: dict)

Bases: athena.transform.feats.base_frontend.BaseFrontend

Add a random signal-to-noise ratio noise or impulse response to clean speech.

classmethod params(config=None)

Set params. :param config: contains nine optional parameters:

--sample_rate

: Sample frequency of waveform data. (int, default = 16000)

--if_add_rir

: If true, add rir to audio data. (bool, default = False)

--rir_filelist

: FileList path of rir.(string, default = ‘rirlist.scp’)

--if_add_noise

: If true, add random noise to audio data. (bool, default = False)

--snr_min

: Minimum SNR adds to signal. (float, default = 0)

--snr_max

: Maximum SNR adds to signal. (float, default = 30)

--noise_filelist

: FileList path of noise.(string, default = ‘noiselist.scp’)

--if_add_aecres

: If true, add aecres to audio data. (bool, default = False)

--aecres_filelist

: FileList path of aecres.(string, default = ‘aecreslist.scp’)

Returns

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

call(audio_data, sample_rate=None)

Caculate power spectrum or log power spectrum of audio data. :param audio_data: the audio signal from which to compute spectrum.

Should be an (1, N) tensor.

Parameters

sample_rate – [option]the samplerate of the signal we working with, default is 16kHz.

Returns

A float tensor of size N containing add-noise audio.