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import os |
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import argparse |
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from SenseVoiceAx import SenseVoiceAx |
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import librosa |
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import numpy as np |
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import time |
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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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"--input", "-i", required=True, type=str, help="Input audio file" |
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) |
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parser.add_argument( |
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"--language", |
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"-l", |
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required=False, |
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type=str, |
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default="auto", |
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choices=["auto", "zh", "en", "yue", "ja", "ko"], |
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) |
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parser.add_argument("--streaming", action="store_true") |
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return parser.parse_args() |
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def main(): |
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args = get_args() |
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input_audio = args.input |
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language = args.language |
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use_itn = True |
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if not args.streaming: |
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max_len = 256 |
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model_path = os.path.join("sensevoice_ax650", "sensevoice.axmodel") |
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else: |
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max_len = 26 |
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model_path = os.path.join("sensevoice_ax650", "streaming_sensevoice.axmodel") |
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assert os.path.exists(model_path), f"model {model_path} not exist" |
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print(f"input_audio: {input_audio}") |
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print(f"language: {language}") |
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print(f"use_itn: {use_itn}") |
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print(f"model_path: {model_path}") |
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print(f"streaming: {args.streaming}") |
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pipeline = SenseVoiceAx( |
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model_path, |
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max_len=max_len, |
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beam_size=3, |
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language="auto", |
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hot_words=None, |
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use_itn=True, |
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streaming=args.streaming, |
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) |
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if not args.streaming: |
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asr_res = pipeline.infer(input_audio, print_rtf=True) |
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print("ASR result: " + asr_res) |
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else: |
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samples, sr = librosa.load(input_audio, sr=16000) |
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samples = (samples * 32768).tolist() |
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duration = len(samples) / 16000 |
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start = time.time() |
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step = int(0.1 * sr) |
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for i in range(0, len(samples), step): |
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is_last = i + step >= len(samples) |
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for res in pipeline.stream_infer(samples[i : i + step], is_last): |
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print(res) |
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end = time.time() |
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cost_time = end - start |
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print(f"RTF: {cost_time / duration}") |
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if __name__ == "__main__": |
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main() |
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