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Update app.py
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app.py
CHANGED
@@ -188,8 +188,9 @@ def add_voice_labelv2(json_file, audio_path):
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speech_prob = model(chunk, SAMPLING_RATE).item()
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speech_probs.append(speech_prob)
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vad_iterator.reset_states() # reset model states after each audio
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-
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voice_idxs = np.where(np.array(speech_probs) >= 0.7)
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if len(voice_idxs) == 0:
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print("NO VOICE SEGMENTS DETECTED!")
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try:
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@@ -202,7 +203,7 @@ def add_voice_labelv2(json_file, audio_path):
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begin_seq = False
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if voice_idxs[i+1] == voice_idxs[i]+1:
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continue
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-
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start_time = float((start_idx*window_size_samples)/SAMPLING_RATE)
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end_time = float((voice_idxs[i]*window_size_samples)/SAMPLING_RATE)
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@@ -210,7 +211,8 @@ def add_voice_labelv2(json_file, audio_path):
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end_minutes = int(end_time)
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start_seconds = (start_time - start_minutes) * 60
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end_seconds = (end_time - end_minutes) * 60
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-
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data['vocal_times'] = {
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"start_time": f"{start_minutes}.{start_seconds:.2f}",
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"end_time": f"{end_minutes}.{end_seconds:.2f}"
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@@ -224,6 +226,7 @@ def add_voice_labelv2(json_file, audio_path):
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print(f"An exception occurred: {e}")
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with open(json_file, 'w') as f:
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json.dump(data, f, indent=4)
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with gr.Blocks() as demo:
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speech_prob = model(chunk, SAMPLING_RATE).item()
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speech_probs.append(speech_prob)
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vad_iterator.reset_states() # reset model states after each audio
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+
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voice_idxs = np.where(np.array(speech_probs) >= 0.7)
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print(len(np.where(np.array(speech_probs) >= 0.7))
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if len(voice_idxs) == 0:
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print("NO VOICE SEGMENTS DETECTED!")
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try:
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begin_seq = False
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if voice_idxs[i+1] == voice_idxs[i]+1:
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continue
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+
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start_time = float((start_idx*window_size_samples)/SAMPLING_RATE)
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end_time = float((voice_idxs[i]*window_size_samples)/SAMPLING_RATE)
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end_minutes = int(end_time)
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start_seconds = (start_time - start_minutes) * 60
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end_seconds = (end_time - end_minutes) * 60
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+
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print("modifying json data... \n")
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data['vocal_times'] = {
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"start_time": f"{start_minutes}.{start_seconds:.2f}",
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"end_time": f"{end_minutes}.{end_seconds:.2f}"
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print(f"An exception occurred: {e}")
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with open(json_file, 'w') as f:
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print("writing_to_json...")
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json.dump(data, f, indent=4)
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with gr.Blocks() as demo:
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