from malaya_speech.supervised import separation
from herpetologist import check_type
from malaya_speech.utils import describe_availability
import logging
logger = logging.getLogger(__name__)
_availability = {
'fastsep-2': {
'Size (MB)': 78.7,
'Quantized Size (MB)': 20.5,
'SISNR PIT': 14.156882,
},
'fastsep-4': {
'Size (MB)': 155,
'Quantized Size (MB)': 40.2,
'SISNR PIT': 19.6825,
},
'fastsep-6': {
'Size (MB)': 231,
'Quantized Size (MB)': 60,
'SISNR PIT': 15.0647,
},
}
[docs]def available_deep_wav():
"""
List available FastSep models trained on raw 8k wav.
"""
logger.info('Tested on 1k samples')
return describe_availability(_availability)
[docs]@check_type
def deep_wav(model: str = 'fastsep-4', quantized: bool = False, **kwargs):
"""
Load FastSep model, trained on raw 8k wav using SISNR PIT loss.
Parameters
----------
model : str, optional (default='fastsep-4')
Check available models at `malaya_speech.multispeaker_separation.available_deep_wav()`.
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.tf.Split class
"""
model = model.lower()
if model not in _availability:
raise ValueError(
'model not supported, please check supported models from `malaya_speech.multispeaker_separation.available_deep_wav()`.'
)
return separation.load(
model=model,
module='multispeaker-separation-wav',
quantized=quantized,
**kwargs
)
