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import aeneas.globalconstants as gc |
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import pandas as pd |
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import os |
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import argparse |
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from aeneas.executetask import ExecuteTask |
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from aeneas.language import Language |
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from aeneas.syncmap import SyncMapFormat |
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from aeneas.task import Task |
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from aeneas.task import TaskConfiguration |
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from aeneas.textfile import TextFileFormat |
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from pydub import AudioSegment |
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parser = argparse.ArgumentParser(description='A program to download all the chapters in a given librivox URL.') |
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parser.add_argument("--text_dir", |
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help='Directory containing the txt files to allign the audio to', |
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required=True, |
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type=str) |
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parser.add_argument("--audio_path", |
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help="path to the chapter which are to be aligned.", |
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required=True, |
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type=str) |
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parser.add_argument("--aeneas_path", |
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help="path to save the allignments from aeneas", |
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required=True, |
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type=str) |
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parser.add_argument("--en_audio_export_path", |
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help="path to save the english audio fragments", |
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required=True, |
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type=str) |
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parser.add_argument("--total_alignment_path", |
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help="path to save the english audio fragments", |
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required=True, |
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type=str) |
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parser.add_argument("--librivoxdeen_alignment", |
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help="path to TSV file provided by LibriVoxDeEn for this particular book", |
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required=True, |
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type=str) |
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parser.add_argument("--aeneas_head_max", |
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help="max value (s) of the head for the aeneas alignment, depending on the book to be alligned this has to be tuned", |
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default = 0, |
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required=False, |
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type=int) |
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parser.add_argument("--aeneas_tail_min", |
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help="min value (s) of the tail for the aeneas alignment, depending on the book to be alligned this has to be tuned", |
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default = 0, |
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required=False, |
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type=int) |
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args = parser.parse_args() |
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number_files = len(os.listdir(args.text_dir)) |
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txt_files = os.listdir(args.text_dir) |
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txt_files.sort() |
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audio_files = os.listdir(args.audio_path) |
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audio_files.sort() |
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EN_AUDIO_EXPORT_NAME = '000{}-{}.wav' |
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EN_ALIGNED_CSV = '000{}-undine_map.csv' |
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TOTAL_ALIGNMENT_NAME = '000{}-undine_map_DeEn.csv' |
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GE_AUDIO_NAME_TEMPLATE = '000{}-undine_{}.flac' |
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tsv_audio_template = "000{}" |
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total_missing = 0 |
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total = 0 |
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if not os.path.exists(args.aeneas_path): |
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os.makedirs(args.aeneas_path) |
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print('made new directory at:',args.aeneas_path) |
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if not os.path.exists(args.en_audio_export_path): |
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os.makedirs(args.en_audio_export_path) |
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print('made new directory at:',args.en_audio_export_path) |
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if not os.path.exists(args.total_alignment_path): |
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os.makedirs(args.total_alignment_path) |
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print('made new directory at:',args.total_alignment_path) |
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for chap in range(1 ,number_files+1): |
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abs_path = args.text_dir+txt_files[chap-1] |
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str_chap = str(chap) |
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str_chap = str(chap).zfill(2) |
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print('start alignent for chap: {}'.format(chap)) |
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config = TaskConfiguration() |
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config[gc.PPN_TASK_LANGUAGE] = Language.ENG |
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config[gc.PPN_TASK_IS_TEXT_FILE_FORMAT] = TextFileFormat.PLAIN |
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config[gc.PPN_TASK_OS_FILE_FORMAT] = SyncMapFormat.CSV |
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config[gc.PPN_TASK_OS_FILE_NAME] = EN_ALIGNED_CSV.format(str_chap) |
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config[gc.PPN_TASK_IS_AUDIO_FILE_DETECT_HEAD_MAX] = args.aeneas_head_max |
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config[gc.PPN_TASK_IS_AUDIO_FILE_DETECT_TAIL_MIN] = args.aeneas_tail_min |
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config[gc.PPN_TASK_OS_FILE_HEAD_TAIL_FORMAT] = 'hidden' |
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task = Task() |
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task.configuration = config |
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task.text_file_path_absolute = abs_path |
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task.audio_file_path_absolute = args.audio_path+'/'+audio_files[chap-1] |
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task.sync_map_file_path = EN_ALIGNED_CSV.format(str_chap) |
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ExecuteTask(task).execute() |
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task.output_sync_map_file(os.getcwd()+args.aeneas_path[1:]) |
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print('alignent done for chap: {}'.format(chap)) |
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print('cutting audio for chap: {}'.format(chap)) |
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en_alignment = pd.read_csv(args.aeneas_path+EN_ALIGNED_CSV.format(str_chap), header = None) |
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original = AudioSegment.from_file(args.audio_path+'/'+audio_files[chap-1]) |
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for Name, Start, End, Text in zip(en_alignment.iloc[:,0], en_alignment.iloc[:,1], en_alignment.iloc[:,2], en_alignment.iloc[:,3]): |
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extract = original[Start*1000:End*1000] |
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extract.export(args.en_audio_export_path+EN_AUDIO_EXPORT_NAME.format(str_chap,Name), format="wav") |
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print('done cutting audio for chap: {}'.format(chap)) |
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print('create CSV for chap: {}'.format(chap)) |
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new = pd.DataFrame(columns=['book', 'DE_audio', 'EN_audio', 'score', 'DE_transcript', 'EN_transcript']) |
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ge_alignment = pd.read_table(args.librivoxdeen_alignment) |
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ge_alignment = ge_alignment[ge_alignment['audio'].str.contains(tsv_audio_template.format(str_chap))==True] |
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ge_audio_names = [] |
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for i in range(ge_alignment.shape[0]+1): |
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ge_audio_names.append(GE_AUDIO_NAME_TEMPLATE.format(str_chap,i)) |
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for name in ge_audio_names: |
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ge_index = ge_alignment[ge_alignment['audio']==name].index |
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if len(ge_index) > 0: |
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en_translation = ge_alignment['en_sentence'][ge_index[0]].replace('<MERGE> ', '').strip() |
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en_index = en_alignment[en_alignment.iloc[:, 3] == en_translation.replace('~', '')].index |
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if len(en_index) > 0: |
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ind = ge_index[0] |
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new = new.append({'book': ge_alignment['book'][ind], |
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'DE_audio': ge_alignment['audio'][ind], |
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'EN_audio':'000{}-'.format(str_chap)+en_alignment.iloc[en_index[0],0]+'.wav', |
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'score':ge_alignment['score'][ind], |
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'DE_transcript':ge_alignment['de_sentence'][ind], |
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'EN_transcript': ge_alignment['en_sentence'][ind]}, |
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ignore_index=True) |
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new.to_csv(args.total_alignment_path+'/'+TOTAL_ALIGNMENT_NAME.format(str_chap),index=False) |
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print('files in the DeEn csv: ' + str(new.shape)) |
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print('files in the EN alignment'+str(en_alignment.shape)) |
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print('files in the original DE csv: ' + str(ge_alignment.shape)) |
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missing = ge_alignment.shape[0]-new.shape[0] |
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total_missing += missing |
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print('number of unaligned audio files: '+str(missing)) |
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print('done creating CSV for chap: {}'.format(chap)) |
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total += ge_alignment.shape[0] |
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print('missing: '+str(total_missing)+' out of '+str(total)+' GE files') |
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