from herpetologist import check_type
from malaya_speech.supervised import speechsplit_conversion
from malaya_speech.utils import describe_availability
_availability = {
'pysptk': {
'fastspeechsplit-vggvox-v2': {
'Size (MB)': 232,
'Quantized Size (MB)': 59.2,
},
'fastspeechsplit-v2-vggvox-v2': {
'Size (MB)': 411,
'Quantized Size (MB)': 105,
},
},
'pyworld': {
'fastspeechsplit-vggvox-v2': {
'Size (MB)': 232,
'Quantized Size (MB)': 59.2,
},
'fastspeechsplit-v2-vggvox-v2': {
'Size (MB)': 411,
'Quantized Size (MB)': 105,
},
},
}
f0_modes = ['pysptk', 'pyworld']
def check_f0_mode(f0_mode='pysptk'):
f0_mode = f0_mode.lower()
if f0_mode not in f0_modes:
raise ValueError("`f0_mode` only support one of ['pysptk', 'pyworld']")
return f0_mode
[docs]def available_deep_conversion(f0_mode: str = 'pysptk'):
"""
List available Voice Conversion models.
Parameters
----------
f0_mode : str, optional (default='pysptk')
F0 conversion supported. Allowed values:
* ``'pysptk'`` - https://github.com/r9y9/pysptk, sensitive towards gender.
* ``'pyworld'`` - https://pypi.org/project/pyworld/
"""
f0_mode = check_f0_mode(f0_mode=f0_mode)
return describe_availability(_availability[f0_mode])
[docs]def deep_conversion(
model: str = 'fastspeechsplit-v2-vggvox-v2',
f0_mode: str = 'pysptk',
quantized: bool = False,
**kwargs,
):
"""
Load Voice Conversion model.
Parameters
----------
model : str, optional (default='fastspeechsplit-v2-vggvox-v2')
Check available models at `malaya_speech.speechsplit_conversion.available_deep_conversion(f0_mode = '{f0_mode}')`
f0_mode : str, optional (default='pysptk')
F0 conversion supported. Allowed values:
* ``'pysptk'`` - https://github.com/r9y9/pysptk, sensitive towards gender.
* ``'pyworld'`` - https://pypi.org/project/pyworld/
quantized : bool, optional (default=False)
if True, will load 8-bit quantized model.
Quantized model not necessary faster, totally depends on the machine.
Returns
-------
result : malaya_speech.model.splitter.FastSpeechSplit class
"""
model = model.lower()
f0_mode = check_f0_mode(f0_mode=f0_mode)
if model not in _availability[f0_mode]:
raise ValueError(
"model not supported, please check supported models from `malaya_speech.speechsplit_conversion.available_deep_conversion(f0_mode = '{f0_mode}')`."
)
return speechsplit_conversion.load(
model=model,
module=f'speechsplit-conversion-{f0_mode}',
f0_mode=f0_mode,
quantized=quantized,
**kwargs,
)
