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@@ -25,6 +25,13 @@ speaker_type_dic = {
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#selects TextGrid files only
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files = Path(input_dir).glob('*.TextGrid')
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+#initialize header
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+df = pd.DataFrame(columns= ["speaker_id","segment_offset","mwu_type","transcription","speaker_type",
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+ "segment_onset","vcm_type","addresseee","raw_filename","ling_type","lex_type"])
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+
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+corpus_onset= 0
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+corpus_offset = 0
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+
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#Loop through each textgrid file of the folder
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for file in files:
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@@ -36,9 +43,8 @@ for file in files:
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audio_onset = int(re.split("\D+", file.stem)[1])
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audio_offset = int(re.split("\D+", file.stem)[2])
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- #initialize header
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- df = pd.DataFrame(columns= ["speaker_id","segment_offset","mwu_type","transcription","speaker_type",
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- "segment_onset","vcm_type","addresseee","raw_filename","ling_type","lex_type"])
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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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#loop through all tiers
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for tier in grid.get_tiers():
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@@ -47,19 +53,21 @@ for file in files:
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#populates dataframe
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df = df.append(pd.Series({'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]}), ignore_index= True)
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+
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+
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+#populates speaker_type column
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+df['speaker_type'] = df['speaker_id'].map(speaker_type_dic)
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- #populates speaker_type column
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- df['speaker_type'] = df['speaker_id'].map(speaker_type_dic)
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+#enriches the csv with previously dropped entries corresponsing to the right timestamps
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+orig_df_subset = original_df[(original_df['segment_onset'] >= corpus_onset) &
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+ (original_df['segment_offset'] <= corpus_offset)]
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- #enriches the csv with previously dropped entries corresponsing to the right timestamps
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- orig_df_subset = original_df[(original_df['segment_onset'] >= audio_onset) &
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- (original_df['segment_offset'] <= audio_offset)]
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- df = df.append(orig_df_subset)
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+df = df.append(orig_df_subset)
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- #sort values by segment_onset before exporting
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- df.sort_values(by='segment_onset', inplace= True)
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+#sort values by segment_onset before exporting
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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}/{1}.csv".format(output_path, file.stem), mode = "x", na_rep= "NA", index= False)
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- print("----------------SAVED!-----------------")
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+#exports to csv
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+df.to_csv("{0}/BN.csv".format(output_path), mode = "x", na_rep= "NA", index= False)
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+print("----------------SAVED!-----------------")
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Apfelsaft