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on
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Running
on
Zero
File size: 2,389 Bytes
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#!/usr/bin/env python3
# Copyright (c) 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 argparse
import logging
import torch
from tqdm import tqdm
import onnxruntime
import numpy as np
import torchaudio
import whisper
def main(args):
utt2wav = {}
with open('{}/wav.scp'.format(args.dir)) as f:
for l in f:
l = l.replace('\n', '').split()
utt2wav[l[0]] = l[1]
option = onnxruntime.SessionOptions()
option.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL
option.intra_op_num_threads = 1
providers = ["CUDAExecutionProvider"]
ort_session = onnxruntime.InferenceSession(args.onnx_path, sess_options=option, providers=providers)
utt2speech_token = {}
for utt in tqdm(utt2wav.keys()):
audio, sample_rate = torchaudio.load(utt2wav[utt])
if sample_rate != 16000:
audio = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=16000)(audio)
if audio.shape[1] / 16000 > 30:
logging.warning('do not support extract speech token for audio longer than 30s')
speech_token = []
else:
feat = whisper.log_mel_spectrogram(audio, n_mels=128)
speech_token = ort_session.run(None, {ort_session.get_inputs()[0].name: feat.detach().cpu().numpy(),
ort_session.get_inputs()[1].name: np.array([feat.shape[2]], dtype=np.int32)})[0].flatten().tolist()
utt2speech_token[utt] = speech_token
torch.save(utt2speech_token, '{}/utt2speech_token.pt'.format(args.dir))
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--dir',
type=str)
parser.add_argument('--onnx_path',
type=str)
args = parser.parse_args()
main(args)
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