cosyvoice/utils/file_utils.py

# 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)

    import librosa, torch
    speech, _ = librosa.load(path=wav, sr=target_sr)
    speech = torch.from_numpy(speech).unsqueeze(dim=0)
    return speech