84 lines
2.8 KiB
Python
84 lines
2.8 KiB
Python
"""
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file_name: transcribe
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project_name: DBM
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created: 2020-10-11
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"""
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import pandas as pd
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import numpy as np
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import librosa
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import glob
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from os.path import join
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import logging
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from dbm_lib.dbm_features.raw_features.util import util as ut
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from dbm_lib.dbm_features.raw_features.util import nlp_util as n_util
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logging.basicConfig(level=logging.INFO)
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logger=logging.getLogger()
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formant_dir = 'speech/deepspeech'
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csv_ext = '_transcribe.csv'
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error_txt = 'error: length less than 0.1'
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def calc_transcribe(video_uri, audio_file, out_loc, fl_name, r_config, deep_path, aud_dur):
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"""
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Preparing Formant freq matrix
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Args:
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audio_file: (.wav) parsed audio file; fl_name: input file name
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out_loc: (str) Output directory; r_config: raw variable config
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"""
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text = n_util.process_deepspeech(audio_file, deep_path)
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df_formant = pd.DataFrame([text], columns=[r_config.nlp_transcribe])
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df_formant.replace('', np.nan, regex=True,inplace=True)
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df_formant[r_config.nlp_totalTime] = aud_dur
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df_formant[r_config.err_reason] = 'Pass'# will replace with threshold in future release
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df_formant['dbm_master_url'] = video_uri
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logger.info('Saving Output file {} '.format(out_loc))
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ut.save_output(df_formant, out_loc, fl_name, formant_dir, csv_ext)
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def empty_transcribe(video_uri, out_loc, fl_name, r_config):
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"""
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Preparing empty formant frequency matrix if something fails
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"""
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cols = [r_config.nlp_transcribe, r_config.nlp_totalTime, r_config.err_reason]
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out_val = [[np.nan, np.nan, error_txt]]
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df_fm = pd.DataFrame(out_val, columns = cols)
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df_fm['dbm_master_url'] = video_uri
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logger.info('Saving Output file {} '.format(out_loc))
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ut.save_output(df_fm, out_loc, fl_name, formant_dir, csv_ext)
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def run_transcribe(video_uri, out_dir, r_config, deep_path):
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"""
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Processing all patient's for fetching Formant freq
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---------------
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---------------
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Args:
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video_uri: video path; r_config: raw variable config object
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out_dir: (str) Output directory for processed output; deep_path: deepspeech build path
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"""
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try:
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input_loc, out_loc, fl_name = ut.filter_path(video_uri, out_dir)
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aud_filter = glob.glob(join(input_loc, fl_name + '.wav'))
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if len(aud_filter)>0:
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audio_file = aud_filter[0]
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aud_dur = librosa.get_duration(filename=audio_file)
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if float(aud_dur) < 0.1:
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logger.info('Output file {} size is less than 0.1 sec'.format(audio_file))
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empty_transcribe(video_uri, out_loc, fl_name, r_config)
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return
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calc_transcribe(video_uri, audio_file, out_loc, fl_name, r_config, deep_path, aud_dur)
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except Exception as e:
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logger.error('Failed to process audio file')
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