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@@ -52,14 +52,20 @@ for file in files:
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if(audio_onset < corpus_onset): corpus_onset = audio_onset
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if(audio_offset > corpus_offset): corpus_offset = audio_offset
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+
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#loop through all tiers
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for tier in grid.get_tiers():
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+
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+ #remove all phones
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+ if 'phones' in tier.name: continue
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+
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for interval in tier.get_all_intervals():
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+ #conditions to skip this iteration: empty, "sp", "sil" or if interval is a phone
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if not interval[2]: continue
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- if interval[2] == "sil" :
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- continue
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-
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+ if interval[2] == "sil" : continue
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+ if interval[2] == "sp" : continue
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+
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#populates dataframe
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temp_dict = {'speaker_id': tier.name, 'segment_onset': (interval[0]*1000 + audio_onset),
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'segment_offset': (interval[1]*1000 + audio_onset), 'transcription': interval[2]}
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@@ -85,5 +91,5 @@ df = pd.concat([df, orig_df_subset])
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df.sort_values(by='segment_onset', inplace= True)
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#exports to csv
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-df.to_csv("{0}/BN32_010007-aligned.csv.csv".format(output_path), mode = "x", na_rep= "NA", index= False)
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+df.to_csv("{0}/BN32_010007-aligned.csv".format(output_path), mode = "x", na_rep= "NA", index= False)
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print("----------------SAVED!-----------------")
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