Update custom_interface_app.py
Browse files- custom_interface_app.py +6 -6
custom_interface_app.py
CHANGED
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@@ -137,7 +137,7 @@ class ASR(Pretrained):
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# Get audio length in seconds
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audio_length = len(waveform) / sr
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if audio_length >=
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print(f"Audio is too long ({audio_length:.2f} seconds), splitting into segments")
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# Detect non-silent segments
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@@ -146,7 +146,7 @@ class ASR(Pretrained):
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segments = []
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current_segment = []
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current_length = 0
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max_duration =
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for interval in non_silent_intervals:
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@@ -204,7 +204,7 @@ class ASR(Pretrained):
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# Get audio length in seconds
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audio_length = len(waveform) / sr
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if audio_length >=
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print(f"Audio is too long ({audio_length:.2f} seconds), splitting into segments")
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# Detect non-silent segments
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@@ -213,7 +213,7 @@ class ASR(Pretrained):
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segments = []
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current_segment = []
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current_length = 0
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max_duration =
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for interval in non_silent_intervals:
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@@ -273,7 +273,7 @@ class ASR(Pretrained):
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# Get audio length in seconds
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audio_length = len(waveform) / sr
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if audio_length >=
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print(f"MMS Audio is too long ({audio_length:.2f} seconds), splitting into segments")
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# Detect non-silent segments
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non_silent_intervals = librosa.effects.split(waveform, top_db=20) # Adjust top_db for sensitivity
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@@ -281,7 +281,7 @@ class ASR(Pretrained):
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segments = []
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current_segment = []
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current_length = 0
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max_duration =
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for interval in non_silent_intervals:
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# Get audio length in seconds
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audio_length = len(waveform) / sr
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if audio_length >= 30:
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print(f"Audio is too long ({audio_length:.2f} seconds), splitting into segments")
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# Detect non-silent segments
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segments = []
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current_segment = []
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current_length = 0
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max_duration = 30 * sr # Maximum segment duration in samples (20 seconds)
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for interval in non_silent_intervals:
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# Get audio length in seconds
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audio_length = len(waveform) / sr
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if audio_length >= 30:
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print(f"Audio is too long ({audio_length:.2f} seconds), splitting into segments")
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# Detect non-silent segments
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segments = []
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current_segment = []
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current_length = 0
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max_duration = 30 * sr # Maximum segment duration in samples (20 seconds)
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for interval in non_silent_intervals:
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# Get audio length in seconds
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audio_length = len(waveform) / sr
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if audio_length >= 30:
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print(f"MMS Audio is too long ({audio_length:.2f} seconds), splitting into segments")
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# Detect non-silent segments
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non_silent_intervals = librosa.effects.split(waveform, top_db=20) # Adjust top_db for sensitivity
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segments = []
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current_segment = []
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current_length = 0
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max_duration = 30 * sr # Maximum segment duration in samples (20 seconds)
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for interval in non_silent_intervals:
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