| 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647 |
- # Copyright (c) 2021 Mobvoi Inc. (authors: Binbin Zhang)
- # 2024 Alibaba Inc (authors: Xiang Lyu)
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- import json
- import torchaudio
- import logging
- logging.getLogger('matplotlib').setLevel(logging.WARNING)
- logging.basicConfig(level=logging.DEBUG,
- format='%(asctime)s %(levelname)s %(message)s')
- def read_lists(list_file):
- lists = []
- with open(list_file, 'r', encoding='utf8') as fin:
- for line in fin:
- lists.append(line.strip())
- return lists
- def read_json_lists(list_file):
- lists = read_lists(list_file)
- results = {}
- for fn in lists:
- with open(fn, 'r', encoding='utf8') as fin:
- results.update(json.load(fin))
- return results
- def load_wav(wav, target_sr):
- speech, sample_rate = torchaudio.load(wav)
- speech = speech.mean(dim=0, keepdim=True)
- if sample_rate != target_sr:
- assert sample_rate > target_sr, 'wav sample rate {} must be greater than {}'.format(sample_rate, target_sr)
- speech = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=target_sr)(speech)
- return speech
|