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speech-scoring
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computing spectrogram for existing files

master
Malar Kannan 2017-11-06 12:15:12 +05:30
parent 22d353f101
commit 5ff437b095
1 changed files with 4 additions and 5 deletions
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speech_data.py
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@ -83,11 +83,10 @@ def create_spectrogram_data(audio_group='audio'):
, quoting=csv.QUOTE_NONE)
# audio_samples = audio_samples.loc[audio_samples['word'] ==
# 'sunflowers'].reset_index(drop=True)
file_names = audio_samples.loc[:, 'file'].apply(lambda x: 'outputs/' + audio_group + '/' + x)
audio_samples['file_exists'] = apply_by_multiprocessing(file_names,os.path.exists)
audio_samples = audio_samples[audio_samples['file_exists'] == False]
audio_samples['spectrogram'] = apply_by_multiprocessing(file_names,generate_aiff_spectrogram)#.apply(
#generate_aiff_spectrogram)
audio_samples['file_paths'] = audio_samples.loc[:, 'file'].apply(lambda x: 'outputs/' + audio_group + '/' + x)
audio_samples['file_exists'] = apply_by_multiprocessing(audio_samples['file_paths'], os.path.exists)
audio_samples = audio_samples[audio_samples['file_exists'] == True].reset_index()
audio_samples['spectrogram'] = apply_by_multiprocessing(audio_samples['file_paths'],generate_aiff_spectrogram)#.apply(
audio_samples['window_count'] = audio_samples.loc[:,'spectrogram'].apply(lambda x: x.shape[0])
audio_samples.to_pickle('outputs/{}-spectrogram.pkl'.format(audio_group))