82 lines
2.6 KiB
Python
82 lines
2.6 KiB
Python
# Copyright 2018 Mycroft AI Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from os.path import isfile
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import json
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from collections import namedtuple
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from math import floor
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import numpy as np
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def _create_listener_params():
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cls = namedtuple('ListenerParams',
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'window_t hop_t buffer_t sample_rate sample_depth n_mfcc n_filt n_fft')
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cls.buffer_samples = property(
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lambda s: s.hop_samples * (int(np.round(s.sample_rate * s.buffer_t)) // s.hop_samples)
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)
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cls.n_features = property(
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lambda s: 1 + int(floor((s.buffer_samples - s.window_samples) / s.hop_samples))
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)
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cls.window_samples = property(lambda s: int(s.sample_rate * s.window_t + 0.5))
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cls.hop_samples = property(lambda s: int(s.sample_rate * s.hop_t + 0.5))
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cls.max_samples = property(lambda s: int(s.buffer_t * s.sample_rate))
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cls.feature_size = property(lambda s: s.n_mfcc)
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return cls
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class Proxy:
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def __init__(self, obj):
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self.obj = obj
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def __getattr__(self, item):
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return getattr(self.obj, item)
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def __setattr__(self, key, value):
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if key == 'obj':
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object.__setattr__(self, key, value)
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else:
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raise AttributeError('Cannot set attributes to proxy')
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def __hash__(self):
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return self.obj.__hash__()
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ListenerParams = _create_listener_params()
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# Reference to global listener parameters
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pr = Proxy(ListenerParams(
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window_t=0.1, hop_t=0.05, buffer_t=1.5, sample_rate=16000,
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sample_depth=2, n_mfcc=13, n_filt=20, n_fft=512
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)) # type: ListenerParams
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def inject_params(model_name: str) -> ListenerParams:
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"""Set the global listener params to a saved model"""
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params_file = model_name + '.params'
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try:
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with open(params_file) as f:
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pr.obj = ListenerParams(**json.load(f))
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except (OSError, ValueError, TypeError):
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if isfile(model_name):
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print('Warning: Failed to load parameters from ' + params_file)
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return pr
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def save_params(model_name: str):
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"""Save current global listener params to a file"""
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with open(model_name + '.params', 'w') as f:
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json.dump(pr._asdict(), f)
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