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| Original file line number | Diff line number | Diff line change |
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| # File description | ||
|
|
||
| - [./http_server.py](./http_server.py) It defines which files to server. | ||
| Files are saved in [./web](./web). | ||
| - [non_streaming_server.py](./non_streaming_server.py) WebSocket server for | ||
| non-streaming models. | ||
| - [vad-remove-non-speech-segments.py](./vad-remove-non-speech-segments.py) It uses | ||
| [silero-vad](https://github.com/snakers4/silero-vad) to remove non-speech | ||
| segments and concatenate all speech segments into a single one. |
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| #!/usr/bin/env python3 | ||
|
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| """ | ||
| This file shows how to remove non-speech segments | ||
| and merge all speech segments into a large segment | ||
| and save it to a file. | ||
| Usage | ||
| python3 ./vad-remove-non-speech-segments.py \ | ||
| --silero-vad-model silero_vad.onnx | ||
| Please visit | ||
| https://github.com/snakers4/silero-vad/blob/master/files/silero_vad.onnx | ||
| to download silero_vad.onnx | ||
| For instance, | ||
| wget https://github.com/snakers4/silero-vad/raw/master/files/silero_vad.onnx | ||
| """ | ||
|
|
||
| import argparse | ||
| import sys | ||
| import time | ||
| from pathlib import Path | ||
|
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||
| import numpy as np | ||
| import sherpa_onnx | ||
| import soundfile as sf | ||
|
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||
| try: | ||
| import sounddevice as sd | ||
| except ImportError: | ||
| print("Please install sounddevice first. You can use") | ||
| print() | ||
| print(" pip install sounddevice") | ||
| print() | ||
| print("to install it") | ||
| sys.exit(-1) | ||
|
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||
|
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||
| def assert_file_exists(filename: str): | ||
| assert Path(filename).is_file(), ( | ||
| f"{filename} does not exist!\n" | ||
| "Please refer to " | ||
| "https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html to download it" | ||
| ) | ||
|
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||
|
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| def get_args(): | ||
| parser = argparse.ArgumentParser( | ||
| formatter_class=argparse.ArgumentDefaultsHelpFormatter | ||
| ) | ||
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| parser.add_argument( | ||
| "--silero-vad-model", | ||
| type=str, | ||
| required=True, | ||
| help="Path to silero_vad.onnx", | ||
| ) | ||
|
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| return parser.parse_args() | ||
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| def main(): | ||
| devices = sd.query_devices() | ||
| if len(devices) == 0: | ||
| print("No microphone devices found") | ||
| sys.exit(0) | ||
|
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||
| print(devices) | ||
| default_input_device_idx = sd.default.device[0] | ||
| print(f'Use default device: {devices[default_input_device_idx]["name"]}') | ||
|
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| args = get_args() | ||
| assert_file_exists(args.silero_vad_model) | ||
|
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| sample_rate = 16000 | ||
| samples_per_read = int(0.1 * sample_rate) # 0.1 second = 100 ms | ||
|
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| config = sherpa_onnx.VadModelConfig() | ||
| config.silero_vad.model = args.silero_vad_model | ||
| config.sample_rate = sample_rate | ||
|
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| window_size = config.silero_vad.window_size | ||
|
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| buffer = [] | ||
| vad = sherpa_onnx.VoiceActivityDetector(config, buffer_size_in_seconds=30) | ||
|
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| all_samples = [] | ||
|
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| print("Started! Please speak") | ||
|
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||
| try: | ||
| with sd.InputStream(channels=1, dtype="float32", samplerate=sample_rate) as s: | ||
| while True: | ||
| samples, _ = s.read(samples_per_read) # a blocking read | ||
| samples = samples.reshape(-1) | ||
| buffer = np.concatenate([buffer, samples]) | ||
|
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| all_samples = np.concatenate([all_samples, samples]) | ||
|
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| while len(buffer) > window_size: | ||
| vad.accept_waveform(buffer[:window_size]) | ||
| buffer = buffer[window_size:] | ||
| except KeyboardInterrupt: | ||
| print("\nCaught Ctrl + C. Saving & Exiting") | ||
|
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||
| speech_samples = [] | ||
| while not vad.empty(): | ||
| speech_samples.extend(vad.front.samples) | ||
| vad.pop() | ||
|
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| speech_samples = np.array(speech_samples, dtype=np.float32) | ||
|
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| filename_for_speech = time.strftime("%Y%m%d-%H%M%S-speech.wav") | ||
| sf.write(filename_for_speech, speech_samples, samplerate=sample_rate) | ||
|
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| filename_for_all = time.strftime("%Y%m%d-%H%M%S-all.wav") | ||
| sf.write(filename_for_all, all_samples, samplerate=sample_rate) | ||
|
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| print(f"Saved to {filename_for_speech} and {filename_for_all}") | ||
|
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|
|
||
| if __name__ == "__main__": | ||
| main() |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,29 @@ | ||
| # File descriptions | ||
|
|
||
| - [./sherpa-onnx-alsa.cc](./sherpa-onnx-alsa.cc) For Linux only, especially for | ||
| embedded Linux, e.g., Raspberry Pi; it uses a streaming model for real-time | ||
| speech recognition with a microphone. | ||
|
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||
| - [./sherpa-onnx-microphone.cc](./sherpa-onnx-microphone.cc) | ||
| For Linux/Windows/macOS; it uses a streaming model for real-time speech | ||
| recognition with a microphone. | ||
|
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| - [./sherpa-onnx-microphone-offline.cc](./sherpa-onnx-microphone-offline.cc) | ||
| For Linux/Windows/macOS; it uses a non-streaming model for speech | ||
| recognition with a microphone. | ||
|
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||
| - [./sherpa-onnx.cc](./sherpa-onnx.cc) | ||
| It uses a streaming model to decode wave files | ||
|
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||
| - [./sherpa-onnx-offline.cc](./sherpa-onnx-offline.cc) | ||
| It uses a non-streaming model to decode wave files | ||
|
|
||
| - [./online-websocket-server.cc](./online-websocket-server.cc) | ||
| WebSocket server for streaming models. | ||
|
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||
| - [./offline-websocket-server.cc](./offline-websocket-server.cc) | ||
| WebSocket server for non-streaming models. | ||
|
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||
| - [./sherpa-onnx-vad-microphone.cc](./sherpa-onnx-vad-microphone.cc) | ||
| Use silero VAD to detect speeches with a microphone. | ||
|
|
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