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import argparse |
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import os |
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from pathlib import Path |
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import sys |
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pwd = os.path.abspath(os.path.dirname(__file__)) |
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sys.path.append(os.path.join(pwd, "../../")) |
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import librosa |
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import numpy as np |
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import sherpa |
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from scipy.io import wavfile |
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import torch |
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import torchaudio |
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from project_settings import project_path, temp_directory |
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def get_args(): |
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parser = argparse.ArgumentParser() |
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parser.add_argument( |
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"--model_dir", |
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default=(project_path / "pretrained_models/huggingface/csukuangfj/wenet-chinese-model").as_posix(), |
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type=str |
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) |
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parser.add_argument( |
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"--filename", |
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default=(project_path / "data/test_wavs/paraformer-zh/si_chuan_hua.wav").as_posix(), |
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type=str |
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) |
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parser.add_argument("--sample_rate", default=16000, type=int) |
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args = parser.parse_args() |
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return args |
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def main(): |
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args = get_args() |
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model_dir = Path(args.model_dir) |
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nn_model_file = model_dir / "final.zip" |
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tokens_file = model_dir / "units.txt" |
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print("nn_model_file: {}".format(nn_model_file)) |
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print("tokens_file: {}".format(tokens_file)) |
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feat_config = sherpa.FeatureConfig(normalize_samples=False) |
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feat_config.fbank_opts.frame_opts.samp_freq = args.sample_rate |
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feat_config.fbank_opts.mel_opts.num_bins = 80 |
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feat_config.fbank_opts.frame_opts.dither = 0 |
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config = sherpa.OfflineRecognizerConfig( |
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nn_model=nn_model_file.as_posix(), |
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tokens=tokens_file.as_posix(), |
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use_gpu=False, |
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feat_config=feat_config, |
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decoding_method="greedy_search", |
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num_active_paths=2, |
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) |
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recognizer = sherpa.OfflineRecognizer(config) |
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signal, sample_rate = librosa.load(args.filename, sr=args.sample_rate) |
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signal *= 32768.0 |
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signal = np.array(signal, dtype=np.int16) |
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temp_file = temp_directory / "temp.wav" |
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wavfile.write( |
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temp_file.as_posix(), |
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rate=args.sample_rate, |
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data=signal |
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) |
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s = recognizer.create_stream() |
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s.accept_wave_file( |
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temp_file.as_posix() |
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) |
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recognizer.decode_stream(s) |
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text = s.result.text.strip() |
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text = text.lower() |
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print("text: {}".format(text)) |
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return |
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if __name__ == "__main__": |
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main() |
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