def params(cls, config=None):
"""
Set params.
:param config: contains nine 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)
---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)
--dither : Dithering constant (0.0 means no dither).
(float, default = 1) [add robust to training]
: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
snip_edges = 1
raw_energy = 1
preEph_coeff = 0.97
window_type = "povey"
remove_dc_offset = True
is_fbank = False
dither = 0.0
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("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("dither", dither)
# cmvn
hparams.append(CMVN.params())
if config is not None:
hparams.parse(config, True)
hparams.type = "Spectrum"
return hparams
def test_cmvn(self):
dim = 40
cmvn = CMVN.params(
{"mean": np.zeros(dim).tolist(), "variance": np.ones(dim).tolist()}
).instantiate()
audio_feature = tf.random_uniform(shape=[3, 40], dtype=tf.float32, maxval=1.0)
print(audio_feature)
normalized = cmvn(audio_feature)
print("normalized = ", normalized)
print("dim is ", cmvn.dim())
cmvn = CMVN.params(
{
"mean": np.zeros(dim).tolist(),
"variance": np.ones(dim).tolist(),
"cmvn": False,
}
).instantiate()
normalized = cmvn(audio_feature)
self.assertAllClose(audio_feature, normalized)
def __init__(self, config: dict):
super().__init__(config)
self.spect = Spectrum(config)
self.cmvn = CMVN(config)
# global cmvn dim == feature dim
if config.type == 'MelSpectrum' and self.cmvn.global_cmvn:
assert config.filterbank_channel_count * config.channel == len(config.global_mean), \
'Error, feature dim {} is not equals to cmvn dim {}'. \
format(config.filterbank_channel_count * config.channel,
len(config.global_mean))
def __init__(self, config: dict):
super().__init__(config)
self.spect = Spectrum(config)
self.cmvn = CMVN(config)
# global cmvn dim == feature dim
if config.type == "Fbank" and self.cmvn.global_cmvn:
assert config.filterbank_channel_count * config.channel == len(
config.global_mean
), "Error, feature dim {} is not equals to cmvn dim {}".format(
config.filterbank_channel_count * config.channel,
len(config.global_mean),
)
print("Fbank params: ", self.config)
def __init__(self, config: dict):
super().__init__(config)
self.cmvn = CMVN(config)
def params(cls, config=None):
"""Set params.
Args:
config: contains the following ten 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 = false)
'output_type': If 1, return power spectrum. If 2, return log-power
spectrum. If 3, return magnitude spectrum. (int, default = 2)
'upper_frequency_limit': High cutoff frequency for mel bins (if <= 0, offset
from Nyquist) (float, default = 0)
'dither': Dithering constant (0.0 means no dither).
(float, default = 1) [add robust to training]
Note:
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
snip_edges = 1
raw_energy = 1
preEph_coeff = 0.97
window_type = "povey"
remove_dc_offset = True
is_fbank = False
dither = 0.0
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("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("dither", dither)
# cmvn
hparams.append(CMVN.params())
if config is not None:
hparams.parse(config, True)
hparams.type = "Spectrum"
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains twenty-nine optional parameters:t
--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)
--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)
hparams.append(CMVN.params())
upper_frequency_limit = 0
lower_frequency_limit = 20.0
filterbank_channel_count = 80.0
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
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
# delta
delta_delta = False # True
order = 2
window = 2
hparams.add_hparam('delta_delta', delta_delta)
hparams.add_hparam('order', order)
hparams.add_hparam('window', window)
hparams.add_hparam('channel', 1)
if hparams.delta_delta:
hparams.channel = hparams.order + 1
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('dither', dither)
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.parse(config, True)
return hparams
def __init__(self, config: dict):
super().__init__(config)
self.fbank = Fbank(config)
self.pitch = Pitch(config)
self.cmvn = CMVN(config)
def params(cls, config=None):
"""Set params.
Args:
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.
"""
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
snip_edges = 1
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
dither = 0.0
delta_delta = False
order = 2
window = 2
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("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)
hparams.add_hparam("dither", dither)
hparams.add_hparam("delta_delta", delta_delta)
hparams.add_hparam("order", order)
hparams.add_hparam("window", window)
hparams.add_hparam("channel", 1)
hparams.append(CMVN.params())
if config is not None:
hparams.parse(config, True)
return hparams
def params(cls, config=None):
"""
Set params.
:param config: contains fourteen 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)
---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)
--use_energy :Use energy (not C0) in MFCC computation.
(bool, default = True)
: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
snip_edges = 1
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
dither = 0.0
delta_delta = False
order = 2
window = 2
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("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)
hparams.add_hparam("dither", dither)
hparams.add_hparam("delta_delta", delta_delta)
hparams.add_hparam("order", order)
hparams.add_hparam("window", window)
hparams.add_hparam("channel", 1)
hparams.append(CMVN.params())
if config is not None:
hparams.parse(config, True)
return hparams