48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
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# Copyright (c) 2021 Mobvoi Inc. (authors: Binbin Zhang)
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# 2024 Alibaba Inc (authors: Xiang Lyu)
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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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import json
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import torchaudio
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import logging
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logging.getLogger('matplotlib').setLevel(logging.WARNING)
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logging.basicConfig(level=logging.DEBUG,
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format='%(asctime)s %(levelname)s %(message)s')
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def read_lists(list_file):
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lists = []
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with open(list_file, 'r', encoding='utf8') as fin:
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for line in fin:
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lists.append(line.strip())
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return lists
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def read_json_lists(list_file):
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lists = read_lists(list_file)
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results = {}
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for fn in lists:
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with open(fn, 'r', encoding='utf8') as fin:
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results.update(json.load(fin))
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return results
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def load_wav(wav, target_sr):
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speech, sample_rate = torchaudio.load(wav)
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speech = speech.mean(dim=0, keepdim=True)
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if sample_rate != target_sr:
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assert sample_rate > target_sr, 'wav sample rate {} must be greater than {}'.format(sample_rate, target_sr)
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speech = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=target_sr)(speech)
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return speech
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