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#
# Copyright © 2025 Agora
# This file is part of TEN Framework, an open source project.
# Licensed under the Apache License, Version 2.0, with certain conditions.
# Refer to the "LICENSE" file in the root directory for more information.
#
import sys, os
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "../include")))
from ten_vad import TenVad
import scipy.io.wavfile as Wavfile
if __name__ == "__main__":
input_file, out_path = sys.argv[1], sys.argv[2]
sr, data = Wavfile.read(input_file)
hop_size = 256 # 16 ms per frame
threshold = 0.5
ten_vad_instance = TenVad(hop_size, threshold) # Create a TenVad instance
num_frames = data.shape[0] // hop_size
# Streaming inference
with open(out_path, "w") as f:
for i in range(num_frames):
audio_data = data[i * hop_size: (i + 1) * hop_size]
out_probability, out_flag = ten_vad_instance.process(audio_data) # Out_flag is speech indicator (0 for non-speech signal, 1 for speech signal)
print("[%d] %0.6f, %d" % (i, out_probability, out_flag))
f.write("[%d] %0.6f, %d\n" % (i, out_probability, out_flag))
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