vad-remove-non-speech-segments.py
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#!/usr/bin/env python3
"""
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/raw/master/src/silero_vad/data/silero_vad.onnx
to download silero_vad.onnx
For instance,
wget https://github.com/snakers4/silero-vad/raw/master/src/silero_vad/data/silero_vad.onnx
"""
import argparse
import sys
import time
from pathlib import Path
import numpy as np
import sherpa_onnx
import soundfile as sf
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)
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"
)
def get_args():
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter
)
parser.add_argument(
"--silero-vad-model",
type=str,
required=True,
help="Path to silero_vad.onnx",
)
return parser.parse_args()
def main():
devices = sd.query_devices()
if len(devices) == 0:
print("No microphone devices found")
print(
"If you are using Linux and you are sure there is a microphone "
"on your system, please use "
"./vad-remove-non-speech-segments-alsa.py"
)
sys.exit(0)
print(devices)
default_input_device_idx = sd.default.device[0]
print(f'Use default device: {devices[default_input_device_idx]["name"]}')
args = get_args()
assert_file_exists(args.silero_vad_model)
sample_rate = 16000
samples_per_read = int(0.1 * sample_rate) # 0.1 second = 100 ms
config = sherpa_onnx.VadModelConfig()
config.silero_vad.model = args.silero_vad_model
config.sample_rate = sample_rate
window_size = config.silero_vad.window_size
buffer = []
vad = sherpa_onnx.VoiceActivityDetector(config, buffer_size_in_seconds=30)
all_samples = []
print("Started! Please speak. Press Ctrl C to exit")
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])
all_samples = np.concatenate([all_samples, samples])
while len(buffer) > window_size:
vad.accept_waveform(buffer[:window_size])
buffer = buffer[window_size:]
except KeyboardInterrupt:
print("\nCaught Ctrl + C. Saving & Exiting")
speech_samples = []
while not vad.empty():
speech_samples.extend(vad.front.samples)
vad.pop()
speech_samples = np.array(speech_samples, dtype=np.float32)
filename_for_speech = time.strftime("%Y%m%d-%H%M%S-speech.wav")
sf.write(filename_for_speech, speech_samples, samplerate=sample_rate)
filename_for_all = time.strftime("%Y%m%d-%H%M%S-all.wav")
sf.write(filename_for_all, all_samples, samplerate=sample_rate)
print(f"Saved to {filename_for_speech} and {filename_for_all}")
if __name__ == "__main__":
main()