def test_hparams(self):
hparams = HParams(cls=self.__class__, name='fbank', n_mels=40)
hparams.del_hparam('cls')
self.assertEqual(hparams.name, 'fbank')
self.assertEqual(hparams.n_mels, 40)
self.assertDictEqual(hparams.values(), {'name': 'fbank', 'n_mels': 40})
hparams.add_hparam('sr', 8000)
self.assertEqual(hparams.sr, 8000)
hparams.set_hparam('sr', 16000)
self.assertEqual(hparams.sr, 16000)
self.assertEqual(hparams.get('sr'), 16000)
hparams.del_hparam('sr')
self.assertJsonEqual(hparams.to_json(),
'{"name": "fbank", "n_mels": 40}')
self.assertEqual('name' in hparams, True)
self.assertEqual(hparams['name'], 'fbank')
self.assertEqual(hparams['n_mels'], 40)
hparams['n_mels'] = 80
self.assertEqual(hparams['n_mels'], 80)
hparams2 = copy.deepcopy(hparams)
self.assertEqual(hparams == hparams2, True)
self.assertEqual(hparams != hparams2, False)
hparams2['name'] = 'MFCC'
self.assertEqual(hparams == hparams2, False)
self.assertEqual(hparams != hparams2, True)
def params(cls, config=None):
"""
Set params.
:param config: contains five optional parameters:
--sample_rate : Waveform data sample frequency (must match the waveform
file, if specified there). (float, default = 16000)
--window_length : Window length in seconds. (float, default = 0.025)
--frame_length : Hop length in seconds. (float, default = 0.010)
--ceps_subband_num : Number of Ceps_subband. (int, default=13).
--tag_ceps_mean_norm : Flag of tag_ceps_mean_norm. (bool, default=True).
:return:An object of class HParams, which is a set of hyperparameters as
name-value pairs.
"""
window_length = 0.025
frame_length = 0.010
ceps_subband_num = 13
tag_ceps_mean_norm = True
sample_rate = 16000
hparams = HParams(cls=cls)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('ceps_subband_num', ceps_subband_num)
hparams.add_hparam('tag_ceps_mean_norm', tag_ceps_mean_norm)
hparams.add_hparam('sample_rate', sample_rate)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains seven optional parameters:upper_frequency_limit(float, default=4000.0),
lower_frequency_limit(float, default=20.0), filterbank_channel_count(float, default=40.0),
window_length(float, default=0.025), frame_length(float, default=0.010),
output_type(int, default=2), sample_rate(float, default=16000).
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
upper_frequency_limit = 4000.0
lower_frequency_limit = 20.0
filterbank_channel_count = 40.0
window_length = 0.025
frame_length = 0.010
output_type = 2
sample_rate = 16000.0
hparams = HParams(cls=cls)
hparams.add_hparam('upper_frequency_limit', upper_frequency_limit)
hparams.add_hparam('lower_frequency_limit', lower_frequency_limit)
hparams.add_hparam('filterbank_channel_count',
filterbank_channel_count)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('output_type', output_type)
hparams.add_hparam('sample_rate', sample_rate)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains five optional parameters:
--sample_rate : Waveform data sample frequency (must match the waveform
file, if specified there). (float, default = 16000)
--window_length : Window length in seconds. (float, default = 0.025)
--frame_length : Hop length in seconds. (float, default = 0.010)
--snip_edges : If True, the last frame (shorter than window_length)
will be cutoff. If False, 1 // 2 frame_length data will
be padded to data. (int, default = True)
--remove_dc_offset : Subtract mean from waveform on each frame (bool, default = true)
:return:An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
window_length = 0.025
frame_length = 0.010
snip_edges = True
remove_dc_offset = True
sample_rate = 16000
hparams = HParams(cls=cls)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('snip_edges', snip_edges)
hparams.add_hparam('remove_dc_offset', remove_dc_offset)
hparams.add_hparam('sample_rate', sample_rate)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains five optional parameters:window_length(float, default=0.025),
frame_length(float, default=0.010), sample_rate(float, default=16000.0),
ceps_subband_num(int, default=13), tag_ceps_mean_norm(bool, default=True).
:return:An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
window_length = 0.025
frame_length = 0.010
ceps_subband_num = 13
tag_ceps_mean_norm = True
sample_rate = 16000.0
hparams = HParams(cls=cls)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('ceps_subband_num', ceps_subband_num)
hparams.add_hparam('tag_ceps_mean_norm', tag_ceps_mean_norm)
hparams.add_hparam('sample_rate', sample_rate)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config: dict = None):
embedding_size = 512
#hp = HParams(cls=cls)
hp = HParams(cls=cls)
hp.add_hparam('embedding_size', embedding_size)
if config is not None:
hp.override_from_dict(config)
return hp
def params(cls, config=None):
"""
Set params.
:param config: contains four optional parameters:
--sample_rate : Waveform data sample frequency (must match the waveform
file, if specified there). (float, default = 16000)
--window_length : Window length in seconds. (float, default = 0.025)
--frame_length : Hop length in seconds. (float, default = 0.010)
--plp_order : Plp order. (int, default=12).
:return:An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
window_length = 0.025
frame_length = 0.010
plp_order = 12
sample_rate = 16000
hparams = HParams(cls=cls)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('plp_order', plp_order)
hparams.add_hparam('sample_rate', sample_rate)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains one optional parameters:sample_rate(float, default=16000.0).
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
sample_rate = 16000.0
hparams = HParams(cls=cls)
hparams.add_hparam('sample_rate', sample_rate)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains two optional parameters: audio_channels(int, default=1),
sample_rate(int, default=16000).
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
audio_channels = 1
sample_rate = 16000
hparams = HParams(cls=cls)
hparams.add_hparam('audio_channels', audio_channels)
hparams.add_hparam('sample_rate', sample_rate)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains four optional parameters:window_length(float, default=0.025),
frame_length(float, default=0.010), sample_rate(float, default=16000.0),
plp_order(int, default=12).
:return:An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
window_length = 0.025
frame_length = 0.010
plp_order = 12
sample_rate = 16000.0
hparams = HParams(cls=cls)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('plp_order', plp_order)
hparams.add_hparam('sample_rate', sample_rate)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains eight optional parameters:upper_frequency_limit(float, default=4000.0),
lower_frequency_limit(float, default=20.0), filterbank_channel_count(float, default=40.0),
window_length(float, default=0.025), frame_length(float, default=0.010),
thres_autoc(float, default=0.3), output_type(int, default=2), sample_rate(int, default=16000).
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
upper_frequency_limit = 8000.0
lower_frequency_limit = 20.0
filterbank_channel_count = 23.0
window_length = 0.025
frame_length = 0.010
snip_edges = 2
raw_energy = 1
preeph_coeff = 0.97
window_type = 'povey'
remove_dc_offset = True
is_fbank = True
thres_autoc = 0.3
output_type = 1
sample_rate = 16000
hparams = HParams(cls=cls)
hparams.add_hparam('upper_frequency_limit', upper_frequency_limit)
hparams.add_hparam('lower_frequency_limit', lower_frequency_limit)
hparams.add_hparam('filterbank_channel_count',
filterbank_channel_count)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('output_type', output_type)
hparams.add_hparam('sample_rate', sample_rate)
hparams.add_hparam('snip_edges', snip_edges)
hparams.add_hparam('raw_energy', raw_energy)
hparams.add_hparam('preeph_coeff', preeph_coeff)
hparams.add_hparam('window_type', window_type)
hparams.add_hparam('remove_dc_offset', remove_dc_offset)
hparams.add_hparam('is_fbank', is_fbank)
hparams.add_hparam('thres_autoc', thres_autoc)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains fifthteen optional parameters.
--sample_rate : Sample frequency of waveform data. (int, default = 16000)
--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)
---raw_energy : If 1, compute frame energy before preemphasis and windowing. If 2, compute frame energy after preemphasis and windowing. (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)
--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)
--coefficient_count : Number of cepstra in MFCC computation.(int, default = 13)
--cepstral_lifter : Constant that controls scaling of MFCCs.(float, default = 22)
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
upper_frequency_limit = 0.0
lower_frequency_limit = 20.0
filterbank_channel_count = 23.0
window_length = 0.025
frame_length = 0.010
output_type = 1
sample_rate = 16000
snip_edges = True
raw_energy = 1
preeph_coeff = 0.97
window_type = 'povey'
remove_dc_offset = True
is_fbank = True
cepstral_lifter = 22.0
coefficient_count = 13
use_energy = True
hparams = HParams(cls=cls)
hparams.add_hparam('upper_frequency_limit', upper_frequency_limit)
hparams.add_hparam('lower_frequency_limit', lower_frequency_limit)
hparams.add_hparam('filterbank_channel_count',
filterbank_channel_count)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('output_type', output_type)
hparams.add_hparam('sample_rate', sample_rate)
hparams.add_hparam('snip_edges', snip_edges)
hparams.add_hparam('raw_energy', raw_energy)
hparams.add_hparam('preeph_coeff', preeph_coeff)
hparams.add_hparam('window_type', window_type)
hparams.add_hparam('remove_dc_offset', remove_dc_offset)
hparams.add_hparam('is_fbank', is_fbank)
hparams.add_hparam('cepstral_lifter', cepstral_lifter)
hparams.add_hparam('coefficient_count', coefficient_count)
hparams.add_hparam('use_energy', use_energy)
if config is not None:
hparams.override_from_dict(config)
return hparams
def speech_params(sr=16000,
bins=40,
dither=True,
use_delta_deltas=True,
cmvn=False,
cmvn_path=''):
''' feat params '''
p = HParams()
p.add_hparam("audio_sample_rate", sr)
p.add_hparam("audio_channels", 1)
p.add_hparam("audio_preemphasis", 0.97)
if dither:
p.add_hparam("audio_dither", 1.0 / np.iinfo(np.int16).max)
else:
p.add_hparam("audio_dither", 0.0)
p.add_hparam("audio_frame_length", 25.0)
p.add_hparam("audio_frame_step", 10.0)
p.add_hparam("audio_lower_edge_hertz", 20.0)
p.add_hparam("audio_upper_edge_hertz", sr / 2.0)
p.add_hparam("audio_num_mel_bins", bins)
p.add_hparam("audio_add_delta_deltas", use_delta_deltas)
p.add_hparam("num_zeropad_frames", 0)
p.add_hparam("audio_global_cmvn", cmvn)
p.add_hparam("audio_cmvn_path", cmvn_path)
return p
def params(cls, config=None):
"""
Set params.
:param config: contains ten optional parameters.
--sample_rate : Sample frequency of waveform data. (int, default = 16000)
--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)
---raw_energy : If 1, compute frame energy before preemphasis and windowing. If 2, compute frame energy after preemphasis and windowing. (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 = false)
--output_type : If 1, return power spectrum. If 2, return log-power spectrum. (int, default = 2)
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
window_length = 0.025
frame_length = 0.010
output_type = 2
sample_rate = 16000
snip_edges = 2
raw_energy = 1
preeph_coeff = 0.97
window_type = 'povey'
remove_dc_offset = True
is_fbank = False
hparams = HParams(cls=cls)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('output_type', output_type)
hparams.add_hparam('sample_rate', sample_rate)
hparams.add_hparam('snip_edges', snip_edges)
hparams.add_hparam('raw_energy', raw_energy)
hparams.add_hparam('preeph_coeff', preeph_coeff)
hparams.add_hparam('window_type', window_type)
hparams.add_hparam('remove_dc_offset', remove_dc_offset)
hparams.add_hparam('is_fbank', is_fbank)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains thirteen 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 True, the last frame (shorter than window_length) will be
cutoff. If False, 1 // 2 frame_length data will be padded
to data. (bool, default = True)
---raw_energy : If 1, compute frame energy before preemphasis and
windowing. If 2, compute frame energy after
preemphasis and windowing. (int, default = 1)
--preeph_coeff : Coefficient for use in frame-signal preemphasis.
(float, default = 0.0)
--window_type : Type of window ("hamm"|"hann"|"povey"|"rect"|"blac"|"tria").
(string, default = "hann")
--remove_dc_offset : Subtract mean from waveform on each frame.
(bool, default = false)
--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)
--output_type : If 1, return power spectrum. If 2, return log-power
spectrum. If 3, return magnitude spectrum. (int, default = 3)
--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 = 0) [add robust to training]
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
hparams = HParams(cls=cls)
window_length = 0.025
frame_length = 0.010
output_type = 3
is_fbank = True
preeph_coeff = 0.0
window_type = 'hann'
dither = 0.0
remove_dc_offset = False
upper_frequency_limit = 0
lower_frequency_limit = 60
filterbank_channel_count = 40
sample_rate = 16000
snip_edges = True
raw_energy = 1
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('snip_edges', snip_edges)
hparams.add_hparam('raw_energy', raw_energy)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('output_type', output_type)
hparams.add_hparam('is_fbank', is_fbank)
hparams.add_hparam('preeph_coeff', preeph_coeff)
hparams.add_hparam('window_type', window_type)
hparams.add_hparam('dither', dither)
hparams.add_hparam('remove_dc_offset', remove_dc_offset)
hparams.add_hparam('upper_frequency_limit', upper_frequency_limit)
hparams.add_hparam('lower_frequency_limit', lower_frequency_limit)
hparams.add_hparam('filterbank_channel_count',
filterbank_channel_count)
hparams.add_hparam('sample_rate', sample_rate)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains twenty-nine optional parameters:
--sample_rate : Samplerate of the signal we working with.
(int, default = 16000)
--window_length : Window length in seconds. (float, default = 0.025)
--frame_length : Hop length in seconds. (float, default = 0.010)
--snip_edges : If true, the last frame (shorter than window_length) will
be cutoff. If false, 1 // 2 frame_length data will be padded
to data. (bool, default = true)
---raw_energy : If 1, compute frame energy before preemphasis and
windowing. If 2, compute frame energy after preemphasis
and windowing. (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)
--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]
--delta-pitch : Smallest relative change in pitch that our
algorithm measures. (float, default = 0.005)
--frames-per-chunk : Only relevant for offline pitch extraction.
(e.g. compute-kaldi-pitch-feats), you can set it to a
small nonzero value, such as 10, for better feature
compatibility with online decoding (affects energy
normalization in the algorithm) (int, default = 0)
--lowpass-cutoff : cutoff frequency for LowPass filter (Hz).
(float, default = 1000)
--lowpass-filter-width : Integer that determines filter width of lowpass filter,
more gives sharper filter (int, default = 1)
--max-f0 : max. F0 to search for (Hz) (float, default = 400)
--max-frames-latency : Maximum number of frames of latency that we allow pitch
tracking to introduce into the feature processing
(affects output only if --frames-per-chunk > 0 and
--simulate-first-pass-online=true (int, default = 0)
--min-f0 : min. F0 to search for (Hz) (float, default = 50)
--nccf-ballast : Increasing this factor reduces NCCF for quiet frames.
(float, default = 7000)
--nccf-ballast-online : This is useful mainly for debug; it affects how the
NCCF ballast is computed. (bool, default = false)
--penalty-factor : cost factor for FO change. (float, default = 0.1)
--preemphasis-coefficient : Coefficient for use in signal preemphasis (deprecated)
(float, default = 0)
--recompute-frame : Only relevant for online pitch extraction, or for
compatibility with online pitch extraction. A
non-critical parameter; the frame at which we recompute
some of the forward pointers, after revising our
estimate of the signal energy. Relevant
if--frames-per-chunk > 0. (int, default = 500)
--resample-frequency : Frequency that we down-sample the signal to. Must be
more than twice lowpass-cutoff (float, default = 4000)
--simulate-first-pass-online : If true, compute-kaldi-pitch-feats will output features
that correspond to what an online decoder would see in
the first pass of decoding-- not the final version of
the features, which is the default. Relevant if
--frames-per-chunk > 0 (bool, default = false)
--soft-min-f0 : Minimum f0, applied in soft way, must not exceed
min-f0 (float, default = 10)
--upsample-filter-width : Integer that determines filter width when upsampling
NCCF (int, default = 5)
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
hparams = HParams(cls=cls)
upper_frequency_limit = 0
lower_frequency_limit = 20.0
filterbank_channel_count = 23.0
window_length = 0.025
frame_length = 0.010
raw_energy = 1
preeph_coeff = 0.97
window_type = 'povey'
remove_dc_offset = True
is_fbank = True
output_type = 1
dither = 0.0
sample_rate = 16000
snip_edges = True
preemph_coeff = 0.0
min_f0 = 50.0
max_f0 = 400.0
soft_min_f0 = 10.0
penalty_factor = 0.1
lowpass_cutoff = 1000.0
resample_freq = 4000.0
delta_pitch = 0.005
nccf_ballast = 7000.0
lowpass_filter_width = 1
upsample_filter_width = 5
max_frames_latency = 0
frames_per_chunk = 0
simulate_first_pass_online = False
recompute_frame = 500
nccf_ballast_online = False
is_log10 = False
pitch_scale = 2.0
pov_scale = 2.0
pov_offset = 0.0
delta_pitch_scale = 10.0
delta_pitch_noise_stddev = 0.005
normalization_left_context = 75
normalization_right_context = 75
delta_window = 2
delay = 0
add_pov_feature = True
add_normalized_log_pitch = True
add_delta_pitch = True
add_raw_log_pitch = False
hparams.add_hparam('sample_rate', sample_rate)
hparams.add_hparam('snip_edges', snip_edges)
hparams.add_hparam('preemph_coeff', preemph_coeff)
hparams.add_hparam('dither', dither)
hparams.add_hparam('min_f0', min_f0)
hparams.add_hparam('max_f0', max_f0)
hparams.add_hparam('soft_min_f0', soft_min_f0)
hparams.add_hparam('penalty_factor', penalty_factor)
hparams.add_hparam('lowpass_cutoff', lowpass_cutoff)
hparams.add_hparam('resample_freq', resample_freq)
hparams.add_hparam('delta_pitch', delta_pitch)
hparams.add_hparam('nccf_ballast', nccf_ballast)
hparams.add_hparam('lowpass_filter_width', lowpass_filter_width)
hparams.add_hparam('upsample_filter_width', upsample_filter_width)
hparams.add_hparam('max_frames_latency', max_frames_latency)
hparams.add_hparam('frames_per_chunk', frames_per_chunk)
hparams.add_hparam('simulate_first_pass_online',
simulate_first_pass_online)
hparams.add_hparam('recompute_frame', recompute_frame)
hparams.add_hparam('nccf_ballast_online', nccf_ballast_online)
hparams.add_hparam('upper_frequency_limit', upper_frequency_limit)
hparams.add_hparam('lower_frequency_limit', lower_frequency_limit)
hparams.add_hparam('filterbank_channel_count',
filterbank_channel_count)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('output_type', output_type)
hparams.add_hparam('raw_energy', raw_energy)
hparams.add_hparam('preeph_coeff', preeph_coeff)
hparams.add_hparam('window_type', window_type)
hparams.add_hparam('remove_dc_offset', remove_dc_offset)
hparams.add_hparam('is_fbank', is_fbank)
hparams.add_hparam('is_log10', is_log10)
hparams.add_hparam('pitch_scale', pitch_scale)
hparams.add_hparam('pov_offset', pov_offset)
hparams.add_hparam('pov_scale', pov_scale)
hparams.add_hparam('delta_pitch_scale', delta_pitch_scale)
hparams.add_hparam('delta_pitch_noise_stddev',
delta_pitch_noise_stddev)
hparams.add_hparam('normalization_left_context',
normalization_left_context)
hparams.add_hparam('normalization_right_context',
normalization_right_context)
hparams.add_hparam('delta_window', delta_window)
hparams.add_hparam('delay', delay)
hparams.add_hparam('add_pov_feature', add_pov_feature)
hparams.add_hparam('add_normalized_log_pitch',
add_normalized_log_pitch)
hparams.add_hparam('add_delta_pitch', add_delta_pitch)
hparams.add_hparam('add_raw_log_pitch', add_raw_log_pitch)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, 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')
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
sample_rate = 16000
if_add_rir = False
rir_filelist = 'rirlist.scp'
if_add_noise = False
noise_filelist = 'noiselist.scp'
snr_min = 0
snr_max = 30
if_add_aecres = False
aecres_filelist = 'aecreslist.scp'
hparams = HParams(cls=cls)
hparams.add_hparam('sample_rate', sample_rate)
hparams.add_hparam('if_add_rir', if_add_rir)
hparams.add_hparam('if_add_noise', if_add_noise)
hparams.add_hparam('rir_filelist', rir_filelist)
hparams.add_hparam('noise_filelist', noise_filelist)
hparams.add_hparam('snr_min', snr_min)
hparams.add_hparam('snr_max', snr_max)
hparams.add_hparam('if_add_aecres', if_add_aecres)
hparams.add_hparam('aecres_filelist', aecres_filelist)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains nineteen optional parameters:
--sample_rate : Waveform data sample frequency (must match the waveform
file, if specified there). (float, default = 16000)
--delta-pitch : Smallest relative change in pitch that our algorithm
measures (float, default = 0.005)
--window_length : Frame length in seconds (float, default = 0.025)
--frame_length : Frame shift in seconds (float, default = 0.010)
--frames-per-chunk : Only relevant for offline pitch extraction (e.g.
compute-kaldi-pitch-feats), you can set it to a small
nonzero value, such as 10, for better feature
compatibility with online decoding (affects energy
normalization in the algorithm) (int, default = 0)
--lowpass-cutoff : cutoff frequency for LowPass filter (Hz).
(float, default = 1000)
--lowpass-filter-width : Integer that determines filter width of lowpass filter,
more gives sharper filter (int, default = 1)
--max-f0 : max. F0 to search for (Hz) (float, default = 400)
--max-frames-latency : Maximum number of frames of latency that we allow pitch
tracking to introduce into the feature processing
(affects output only if --frames-per-chunk > 0 and
--simulate-first-pass-online=true (int, default = 0)
--min-f0 : min. F0 to search for (Hz) (float, default = 50)
--nccf-ballast : Increasing this factor reduces NCCF for quiet frames.
(float, default = 7000)
--nccf-ballast-online : This is useful mainly for debug; it affects how the NCCF
ballast is computed. (bool, default = false)
--penalty-factor : cost factor for FO change. (float, default = 0.1)
--preemphasis-coefficient : Coefficient for use in signal preemphasis (deprecated).
(float, default = 0)
--recompute-frame : Only relevant for online pitch extraction, or for
compatibility with online pitch extraction. A
non-critical parameter; the frame at which we recompute
some of the forward pointers, after revising our
estimate of the signal energy. Relevant
if--frames-per-chunk > 0. (int, default = 500)
--resample-frequency : Frequency that we down-sample the signal to. Must be
more than twice lowpass-cutoff (float, default = 4000)
--simulate-first-pass-online : If true, compute-kaldi-pitch-feats will output features
that correspond to what an online decoder would see in
the first pass of decoding-- not the final version of
the features, which is the default. Relevant if
--frames-per-chunk > 0 (bool, default = false)
--snip-edges : If this is set to false, the incomplete frames near the
ending edge won't be snipped, so that the number of
frames is the file size divided by the frame-shift.
This makes different types of features give the same
number of frames. (bool, default = true)
--soft-min-f0 : Minimum f0, applied in soft way, must not exceed min-f0.
(float, default = 10)
--upsample-filter-width : Integer that determines filter width when upsampling
NCCF. (int, default = 5)
--add-delta-pitch : If true, time derivative of log-pitch is added to
output features. (bool, default = true)
--add-pov-feature : If true, the warped NCCF is added to output features.
(bool, default = true)
--add-raw-log-pitch : If true, log(pitch) is added to output features.
(bool, default = false)
--delay : Number of frames by which the pitch information is
delayed. (int, default = 0)
--delta-pitch-noise-stddev : Standard deviation for noise we add to the delta
log-pitch (before scaling); should be about the same as
delta-pitch option to pitch creation. The purpose is
to get rid of peaks in the delta-pitch caused by
discretization of pitch values. (float, default = 0.005)
--delta-pitch-scale : Term to scale the final delta log-pitch feature.
(float, default = 10)
--delta-window : Number of frames on each side of central frame,
to use for delta window. (int, default = 2)
--normalization-left-context : Left-context (in frames) for moving window
normalization. (int, default = 75)
--normalization-right-context : Right-context (in frames) for moving window
normalization. (int, default = 75)
--pitch-scale : Scaling factor for the final normalized log-pitch
value. (float, default = 2)
--pov-offset : This can be used to add an offset to the POV feature.
Intended for use in online decoding as a substitute
for CMN. (float, default = 0)
--pov-scale : Scaling factor for final POV (probability of voicing)
feature. (float, default = 2)
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
hparams = HParams(cls=cls)
window_length = 0.025
frame_length = 0.010
sample_rate = 16000
snip_edges = True
preemph_coeff = 0.0
min_f0 = 50.0
max_f0 = 400.0
soft_min_f0 = 10.0
penalty_factor = 0.1
lowpass_cutoff = 1000.0
resample_freq = 4000.0
delta_pitch = 0.005
nccf_ballast = 7000.0
lowpass_filter_width = 1
upsample_filter_width = 5
max_frames_latency = 0
frames_per_chunk = 0
simulate_first_pass_online = False
recompute_frame = 500
nccf_ballast_online = False
pitch_scale = 2.0
pov_scale = 2.0
pov_offset = 0.0
delta_pitch_scale = 10.0
delta_pitch_noise_stddev = 0.005
normalization_left_context = 75
normalization_right_context = 75
delta_window = 2
delay = 0
add_pov_feature = True
add_normalized_log_pitch = True
add_delta_pitch = True
add_raw_log_pitch = False
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('sample_rate', sample_rate)
hparams.add_hparam('snip_edges', snip_edges)
hparams.add_hparam('preemph_coeff', preemph_coeff)
hparams.add_hparam('min_f0', min_f0)
hparams.add_hparam('max_f0', max_f0)
hparams.add_hparam('soft_min_f0', soft_min_f0)
hparams.add_hparam('penalty_factor', penalty_factor)
hparams.add_hparam('lowpass_cutoff', lowpass_cutoff)
hparams.add_hparam('resample_freq', resample_freq)
hparams.add_hparam('delta_pitch', delta_pitch)
hparams.add_hparam('nccf_ballast', nccf_ballast)
hparams.add_hparam('lowpass_filter_width', lowpass_filter_width)
hparams.add_hparam('upsample_filter_width', upsample_filter_width)
hparams.add_hparam('max_frames_latency', max_frames_latency)
hparams.add_hparam('frames_per_chunk', frames_per_chunk)
hparams.add_hparam('simulate_first_pass_online',
simulate_first_pass_online)
hparams.add_hparam('recompute_frame', recompute_frame)
hparams.add_hparam('nccf_ballast_online', nccf_ballast_online)
hparams.add_hparam('pitch_scale', pitch_scale)
hparams.add_hparam('pov_offset', pov_offset)
hparams.add_hparam('pov_scale', pov_scale)
hparams.add_hparam('delta_pitch_scale', delta_pitch_scale)
hparams.add_hparam('delta_pitch_noise_stddev',
delta_pitch_noise_stddev)
hparams.add_hparam('normalization_left_context',
normalization_left_context)
hparams.add_hparam('normalization_right_context',
normalization_right_context)
hparams.add_hparam('delta_window', delta_window)
hparams.add_hparam('delay', delay)
hparams.add_hparam('add_pov_feature', add_pov_feature)
hparams.add_hparam('add_normalized_log_pitch',
add_normalized_log_pitch)
hparams.add_hparam('add_delta_pitch', add_delta_pitch)
hparams.add_hparam('add_raw_log_pitch', add_raw_log_pitch)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains seven optional parameters:
--norm_means : Flag of norm_means. (bool, default=True)
--norm_vars : Flag of norm_vars. (bool, default=False)
--utt2spk : Use for speaker CMVN. (string, default=None)
--spk2utt : Rspecifier for speaker to utterance-list map.
(string, default=None)
--reverse : Flag of reverse. (bool, default=False)
--std_floor : Floor to std. (float, default=1.0e-20)
--filetype : Type of input file. (string, default='mat')
:return:
"""
norm_means = True
norm_vars = False
utt2spk = None
spk2utt = None
reverse = False
std_floor = 1.0e-20
filetype = 'mat'
hparams = HParams(cls=cls)
hparams.add_hparam('norm_means', norm_means)
hparams.add_hparam('norm_vars', norm_vars)
hparams.add_hparam('utt2spk', utt2spk)
hparams.add_hparam('spk2utt', spk2utt)
hparams.add_hparam('reverse', reverse)
hparams.add_hparam('std_floor', std_floor)
hparams.add_hparam('filetype', filetype)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
norm_means = True
norm_vars = False
utt2spk = None
spk2utt = None
reverse = False
std_floor = 1.0e-20
filetype = 'mat'
hparams = HParams(cls=cls)
hparams.add_hparam('norm_means', norm_means)
hparams.add_hparam('norm_vars', norm_vars)
hparams.add_hparam('utt2spk', utt2spk)
hparams.add_hparam('spk2utt', spk2utt)
hparams.add_hparam('reverse', reverse)
hparams.add_hparam('std_floor', std_floor)
hparams.add_hparam('filetype', filetype)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains twenty optional parameters:
--delta-pitch : Smallest relative change in pitch that our algorithm measures (float, default = 0.005)
--frame-length : Frame length in milliseconds (float, default = 25)
--frame-shift : Frame shift in milliseconds (float, default = 10)
--frames-per-chunk : Only relevant for offline pitch extraction (e.g. compute-kaldi-pitch-feats), you can set it to a small nonzero value, such as 10, for better feature compatibility with online decoding (affects energy normalization in the algorithm) (int, default = 0)
--lowpass-cutoff : cutoff frequency for LowPass filter (Hz) (float, default = 1000)
--lowpass-filter-width : Integer that determines filter width of lowpass filter, more gives sharper filter (int, default = 1)
--max-f0 : max. F0 to search for (Hz) (float, default = 400)
--max-frames-latency : Maximum number of frames of latency that we allow pitch tracking to introduce into the feature processing (affects output only if --frames-per-chunk > 0 and --simulate-first-pass-online=true (int, default = 0)
--min-f0 : min. F0 to search for (Hz) (float, default = 50)
--nccf-ballast : Increasing this factor reduces NCCF for quiet frames (float, default = 7000)
--nccf-ballast-online : This is useful mainly for debug; it affects how the NCCF ballast is computed. (bool, default = false)
--penalty-factor : cost factor for FO change. (float, default = 0.1)
--preemphasis-coefficient : Coefficient for use in signal preemphasis (deprecated) (float, default = 0)
--recompute-frame : Only relevant for online pitch extraction, or for compatibility with online pitch extraction. A non-critical parameter; the frame at which we recompute some of the forward pointers, after revising our estimate of the signal energy. Relevant if--frames-per-chunk > 0 (int, default = 500)
--resample-frequency : Frequency that we down-sample the signal to. Must be more than twice lowpass-cutoff (float, default = 4000)
--sample-frequency : Waveform data sample frequency (must match the waveform file, if specified there) (float, default = 16000)
--simulate-first-pass-online : If true, compute-kaldi-pitch-feats will output features that correspond to what an online decoder would see in the first pass of decoding-- not the final version of the features, which is the default. Relevant if --frames-per-chunk > 0 (bool, default = false)
--snip-edges : If this is set to false, the incomplete frames near the ending edge won't be snipped, so that the number of frames is the file size divided by the frame-shift. This makes different types of features give the same number of frames. (bool, default = true)
--soft-min-f0 : Minimum f0, applied in soft way, must not exceed min-f0 (float, default = 10)
--upsample-filter-width : Integer that determines filter width when upsampling NCCF (int, default = 5)
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
hparams = HParams(cls=cls)
window_length = 0.025
frame_length = 0.010
sample_rate = 16000
snip_edges = True
preemph_coeff = 0.0
min_f0 = 50.0
max_f0 = 400.0
soft_min_f0 = 10.0
penalty_factor = 0.1
lowpass_cutoff = 1000.0
resample_freq = 4000.0
delta_pitch = 0.005
nccf_ballast = 7000.0
lowpass_filter_width = 1
upsample_filter_width = 5
max_frames_latency = 0
frames_per_chunk = 0
simulate_first_pass_online = False
recompute_frame = 500
nccf_ballast_online = False
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('sample_rate', sample_rate)
hparams.add_hparam('snip_edges', snip_edges)
hparams.add_hparam('preemph_coeff', preemph_coeff)
hparams.add_hparam('min_f0', min_f0)
hparams.add_hparam('max_f0', max_f0)
hparams.add_hparam('soft_min_f0', soft_min_f0)
hparams.add_hparam('penalty_factor', penalty_factor)
hparams.add_hparam('lowpass_cutoff', lowpass_cutoff)
hparams.add_hparam('resample_freq', resample_freq)
hparams.add_hparam('delta_pitch', delta_pitch)
hparams.add_hparam('nccf_ballast', nccf_ballast)
hparams.add_hparam('lowpass_filter_width', lowpass_filter_width)
hparams.add_hparam('upsample_filter_width', upsample_filter_width)
hparams.add_hparam('max_frames_latency', max_frames_latency)
hparams.add_hparam('frames_per_chunk', frames_per_chunk)
hparams.add_hparam('simulate_first_pass_online', simulate_first_pass_online)
hparams.add_hparam('recompute_frame', recompute_frame)
hparams.add_hparam('nccf_ballast_online', nccf_ballast_online)
if config is not None:
hparams.override_from_dict(config)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains eight optional parameters:upper_frequency_limit(float, default=4000.0),
lower_frequency_limit(float, default=20.0), filterbank_channel_count(float, default=40.0),
window_length(float, default=0.025), frame_length(float, default=0.010),
thres_autoc(float, default=0.3), output_type(int, default=2), sample_rate(int, default=16000).
:return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
"""
hparams = HParams(cls=cls)
upper_frequency_limit = 0
lower_frequency_limit = 20.0
filterbank_channel_count = 23.0
window_length = 0.025
frame_length = 0.010
raw_energy = 1
preeph_coeff = 0.97
window_type = 'povey'
remove_dc_offset = True
is_fbank = True
output_type = 1
sample_rate = 16000
snip_edges = True
preemph_coeff = 0.0
min_f0 = 50.0
max_f0 = 400.0
soft_min_f0 = 10.0
penalty_factor = 0.1
lowpass_cutoff = 1000.0
resample_freq = 4000.0
delta_pitch = 0.005
nccf_ballast = 7000.0
lowpass_filter_width = 1
upsample_filter_width = 5
max_frames_latency = 0
frames_per_chunk = 0
simulate_first_pass_online = False
recompute_frame = 500
nccf_ballast_online = False
hparams.add_hparam('sample_rate', sample_rate)
hparams.add_hparam('snip_edges', snip_edges)
hparams.add_hparam('preemph_coeff', preemph_coeff)
hparams.add_hparam('min_f0', min_f0)
hparams.add_hparam('max_f0', max_f0)
hparams.add_hparam('soft_min_f0', soft_min_f0)
hparams.add_hparam('penalty_factor', penalty_factor)
hparams.add_hparam('lowpass_cutoff', lowpass_cutoff)
hparams.add_hparam('resample_freq', resample_freq)
hparams.add_hparam('delta_pitch', delta_pitch)
hparams.add_hparam('nccf_ballast', nccf_ballast)
hparams.add_hparam('lowpass_filter_width', lowpass_filter_width)
hparams.add_hparam('upsample_filter_width', upsample_filter_width)
hparams.add_hparam('max_frames_latency', max_frames_latency)
hparams.add_hparam('frames_per_chunk', frames_per_chunk)
hparams.add_hparam('simulate_first_pass_online',
simulate_first_pass_online)
hparams.add_hparam('recompute_frame', recompute_frame)
hparams.add_hparam('nccf_ballast_online', nccf_ballast_online)
hparams.add_hparam('upper_frequency_limit', upper_frequency_limit)
hparams.add_hparam('lower_frequency_limit', lower_frequency_limit)
hparams.add_hparam('filterbank_channel_count',
filterbank_channel_count)
hparams.add_hparam('window_length', window_length)
hparams.add_hparam('frame_length', frame_length)
hparams.add_hparam('output_type', output_type)
hparams.add_hparam('raw_energy', raw_energy)
hparams.add_hparam('preeph_coeff', preeph_coeff)
hparams.add_hparam('window_type', window_type)
hparams.add_hparam('remove_dc_offset', remove_dc_offset)
hparams.add_hparam('is_fbank', is_fbank)
if config is not None:
hparams.override_from_dict(config)
return hparams
