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organizedPairedAudio.py
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organizedPairedAudio.py
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"""
organize paired audio files into simannotator format
"""
from audioLyricsCsvParser import parseCorrespondingAriaCsv
from filepath import *
from src.textgridParser import textGrid2WordList
from lyricsMatch import stringDist
import soundfile as sf
import os
import csv
lines_dan = parseCorrespondingAriaCsv('./corresponding_arias/corresponding pro-amateur arias - dan.csv')
lines_laosheng = parseCorrespondingAriaCsv('./corresponding_arias/corresponding pro-amateur arias - laosheng.csv')
def saveAudio2Path(filename, audio, start_time, end_time, fs):
start_sample = int(start_time*fs)
end_sample = int(end_time*fs)
# wavfile.write(filename, fs, audio[start_sample:end_sample])
sf.write(filename, audio[start_sample:end_sample], fs)
def saveLyrics2Path(filename, lyrics):
with open(filename, 'w') as testfile:
csv_writer = csv.writer(testfile)
csv_writer.writerow(lyrics)
def dictRubric():
rubric = {'Zheng ti Overall': {'rubric': {'ratings': [1, 2, 3, 4]}},
'Fa yin Pronunciation': {'rubric': {'ratings': [1, 2, 3, 4]}},
'Yin diao Intonation': {'rubric': {'ratings': [1, 2, 3, 4]}},
'Qiang ruo Loudness': {'rubric': {'ratings': [1, 2, 3, 4]}},
'Yin se Tone quality': {'rubric': {'ratings': [1, 2, 3, 4]}}}
return rubric
def dictSeg(start_time_overall,
end_time_overall):
seg = {'Zheng ti Overall': [{'start_time': start_time_overall,
'end_time': end_time_overall,
'label': 'Entire_sound'}],
'Fa yin Pronunciation': [{'start_time': start_time_overall,
'end_time': end_time_overall,
'label': 'Entire_sound'}],
'Yin diao Intonation': [{'start_time': start_time_overall,
'end_time': end_time_overall,
'label': 'Entire_sound'}],
'Qiang ruo Loudness': [{'start_time': start_time_overall,
'end_time': end_time_overall,
'label': 'Entire_sound'}],
'Yin se Tone quality': [{'start_time': start_time_overall,
'end_time': end_time_overall,
'label': 'Entire_sound'}]}
return seg
def getFilenames(lines, role):
dict_dataset_description = {}
ii_exercise = 0
for pair in lines:
filename_current_ref_aria = pair[0]+'_'+pair[1]
if pair[0] == role:
path_wav = join(path_dataset_qmUpf_old,'wav')
path_textgrid = path_textgrid_qmUpf_old
else:
path_wav = join(path_dataset_nacta_2017,'wav')
path_textgrid = path_textgrid_nacta_2017
filename_ref = pair[1]
filename_amateur = pair[3]
filename_ref_audio = join(path_wav, pair[0], filename_ref+'.wav')
filename_ref_textgrid = join(path_textgrid, pair[0], filename_ref+'.textgrid')
if pair[2] == role:
path_wav = join(path_dataset_qmUpf_old,'wav')
path_textgrid = path_textgrid_qmUpf_old
else:
path_wav = join(path_dataset_nacta_2017,'wav')
path_textgrid = path_textgrid_nacta_2017
filename_amateur_audio = join(path_wav, pair[2], filename_amateur + '.wav')
filename_amateur_textgrid = join(path_textgrid, pair[2], filename_amateur + '.textgrid')
audio_ref, fs_ref = sf.read(filename_ref_audio)
audio_amateur, fs_amateur = sf.read(filename_amateur_audio)
textgrid_line_ref = textGrid2WordList(filename_ref_textgrid, whichTier='line')
textgrid_line_amateur = textGrid2WordList(filename_amateur_textgrid, whichTier='line')
# clean the parsed lines
textgrid_line_ref = [tlr for tlr in textgrid_line_ref if len(tlr[2])]
textgrid_line_amateur = [tla for tla in textgrid_line_amateur if len(tla[2])]
for ii_ref, line_element_ref in enumerate(textgrid_line_ref):
name_exercise = pair[0] + '_' + filename_ref + '_' + str(ii_ref)
name_exercise = name_exercise[-49:]
for ii_amateur, line_element_amateur in enumerate(textgrid_line_amateur):
if stringDist(line_element_ref[2], line_element_amateur[2]) > 0.7:
print(pair[0]+'_'+filename_ref+'_vs_'+pair[2]+'_'+filename_amateur, str(ii_ref), line_element_ref[2], line_element_amateur[2])
path_ref_amateur_saved_base = join('./corresponding_arias', role, pair[0]+'_' + filename_ref, str(ii_ref))
# + '_vs_' +pair[2]+'_'+ filename_amateur
path_ref_audio_saved = join(path_ref_amateur_saved_base, 'reference')
path_amateur_audio_saved = join(path_ref_amateur_saved_base, 'performances')
if not os.path.exists(path_ref_audio_saved):
os.makedirs(path_ref_audio_saved)
if not os.path.exists(path_amateur_audio_saved):
os.makedirs(path_amateur_audio_saved)
filename_ref_audio_saved = join(path_ref_audio_saved, pair[0]+'_' + filename_ref + '_' + str(ii_ref)+'.wav')
if not os.path.isfile(filename_ref_audio_saved):
# add exercise name to the dataset description dictionary
ii_exercise += 1
dict_dataset_description['exercise ' + str(ii_exercise)] = {
'name': name_exercise, 'recs': []}
saveAudio2Path(filename=filename_ref_audio_saved,
audio=audio_ref,
start_time=line_element_ref[0],
end_time=line_element_ref[1],
fs=fs_ref)
# add the ref_media value
dict_dataset_description['exercise '+str(ii_exercise)]['ref_media'] = filename_ref_audio_saved.replace('./corresponding_arias/'+role+'/', '')
# save the segmentation to json
dict_ref_seg = dictSeg(0,
line_element_ref[1]-line_element_ref[0]-0.1
)
json.dump(dict_ref_seg, open(filename_ref_audio_saved.replace('.wav', '.trans_json'), 'w'))
filename_amateur_audio_saved = join(path_amateur_audio_saved, pair[2] + '_' + filename_amateur + '_' + str(ii_amateur) + '.wav')
saveAudio2Path(filename=filename_amateur_audio_saved,
audio=audio_amateur,
start_time=line_element_amateur[0],
end_time=line_element_amateur[1],
fs=fs_amateur)
# find the key for the ref name, write the path into recs key
key_exercise = None
for key in dict_dataset_description:
if dict_dataset_description[key]['name'] == name_exercise:
key_exercise = key
# add the rec value
name_rec = pair[2]+'_'+filename_amateur+'_'+str(ii_amateur)
name_rec = name_rec[-49:]
dict_dataset_description[key_exercise]['recs'].append({'_id': name_rec,
'path': filename_amateur_audio_saved.replace('./corresponding_arias/'+role+'/', '')})
saveLyrics2Path(filename=join(path_ref_amateur_saved_base, 'lyrics_'+ pair[2]+'_'+filename_amateur+'_'+str(ii_amateur)+'.csv'),
lyrics=[line_element_ref[2], line_element_amateur[2]])
# save the segmentation to json
dict_amateur_seg = dictSeg(0,
line_element_amateur[1]-line_element_amateur[0]-0.1
)
json.dump(dict_amateur_seg, open(filename_amateur_audio_saved.replace('.wav', '.json'), 'w'))
return dict_dataset_description
if __name__ == '__main__':
import json
dict_data_description_laosheng = getFilenames(lines_laosheng, 'laosheng')
json.dump(dict_data_description_laosheng,
open(join('./corresponding_arias/laosheng', 'data.json'), 'w'))
json.dump(dictRubric(),
open(join('./corresponding_arias/laosheng', 'rubric.json'), 'w'))
dict_data_description_danAll = getFilenames(lines_dan, 'danAll')
json.dump(dict_data_description_danAll,
open(join('./corresponding_arias/danAll', 'data.json'), 'w'))
json.dump(dictRubric(),
open(join('./corresponding_arias/danAll', 'rubric.json'), 'w'))