transcription logs
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@@ -126,7 +126,7 @@ def process_speech(transcribe_df,r_config):
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Returns:
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Dataframe for speech features
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"""
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transcribe_df = transcribe_df.replace(np.nan, '', regex=True)
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err_transcribe = transcribe_df[r_config.err_reason].iloc[0]
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transcribe = transcribe_df[r_config.nlp_transcribe].iloc[0]
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total_time = transcribe_df[r_config.nlp_totalTime].iloc[0]
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@@ -158,7 +158,7 @@ def vad_get_segment_times(sample_rate, frame_duration_ms,
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for frame in frames:
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is_speech = vad.is_speech(frame.bytes, sample_rate)
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sys.stdout.write('1' if is_speech else '0')
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#sys.stdout.write('1' if is_speech else '0')
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if not triggered:
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ring_buffer.append((frame, is_speech))
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num_voiced = len([f for f, speech in ring_buffer if speech])
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@@ -167,7 +167,7 @@ def vad_get_segment_times(sample_rate, frame_duration_ms,
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# TRIGGERED state.
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if num_voiced > 0.9 * ring_buffer.maxlen:
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triggered = True
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sys.stdout.write('+(%s)' % (ring_buffer[0][0].timestamp,))
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#sys.stdout.write('+(%s)' % (ring_buffer[0][0].timestamp,))
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start_times.append(ring_buffer[0][0].timestamp) # BT
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ring_buffer.clear()
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else:
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@@ -179,18 +179,18 @@ def vad_get_segment_times(sample_rate, frame_duration_ms,
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# unvoiced, then enter NOTTRIGGERED and yield whatever
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# audio we've collected.
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if num_unvoiced > 0.9 * ring_buffer.maxlen:
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sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration))
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#sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration))
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end_times.append(ring_buffer[0][0].timestamp + frame.duration) # BT
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triggered = False
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if triggered: # BT if were in triggered state at end of signal, set output time
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sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration))
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#sys.stdout.write('-(%s)' % (frame.timestamp + frame.duration))
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if len(ring_buffer)>0:
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end_times.append(ring_buffer[0][0].timestamp ) # BT
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else:
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# only get here in very rare case that we triggered on 2nd-to-last frame
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end_times.append(frame.timestamp + frame.duration)
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sys.stdout.write('\n')
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#sys.stdout.write('\n')
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return(start_times, end_times)
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