Datasets:
File size: 4,211 Bytes
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import os
import gentle
import pandas as pd
import codecs
import logging
def on_progress(p):
for k,v in p.items():
logging.debug("%s: %s" % (k, v))
# DOWNLOAD THE DB AND CHANGE THIS PATH
path='path/to/EmoV-DB_sorted/'
resources = gentle.Resources()
def load_emov_db(path_to_EmoV_DB):
transcript = os.path.join(path_to_EmoV_DB, 'cmuarctic.data')
lines = codecs.open(transcript, 'r', 'utf-8').readlines()
# in our database, we use only files beginning with arctic_a. And the number of these sentences correspond.
# Here we build a dataframe with number and text of each of these lines
sentences = []
for line in lines:
temp = {}
idx_n_0 = line.find('arctic_a') + len('arctic_a')
if line.find('arctic_a') != -1:
print(line)
print(idx_n_0)
idx_n_end = idx_n_0 + 4
number = line[idx_n_0:idx_n_end]
print(number)
temp['n'] = number
idx_text_0 = idx_n_end + 2
text = line.strip()[idx_text_0:-3]
temp['text'] = text
# print(text)
sentences.append(temp)
sentences = pd.DataFrame(sentences)
print(sentences)
speakers=next(os.walk(path_to_EmoV_DB))[1] #this list directories (and not files, contrary to osl.listdir() )
data=[]
for spk in speakers:
emo_cat = next(os.walk(os.path.join(path_to_EmoV_DB,spk)))[1] #this list directories (and not files, contrary to osl.listdir() )
for emo in emo_cat:
for file in os.listdir(os.path.join(path_to_EmoV_DB, spk, emo)):
print(file)
fpath = os.path.join(path_to_EmoV_DB, spk, emo, file)
if file[-4:] == '.wav':
fnumber = file[-8:-4]
print(fnumber)
if fnumber.isdigit():
text = sentences[sentences['n'] == fnumber]['text'].iloc[0] # result must be a string and not a df with a single element
# text_lengths.append(len(text))
# texts.append(text)
# texts.append(np.array(text, np.int32).tostring())
# fpaths.append(fpath)
# emo_cats.append(emo)
e = {'database': 'EmoV-DB',
'id': file[:-4],
'speaker': spk,
'emotion':emo,
'transcription': text,
'sentence_path': fpath}
data.append(e)
print(e)
data = pd.DataFrame.from_records(data)
return data
def align_db(data):
import pathlib
for i, row in data.iterrows():
f = row.sentence_path
transcript = row.transcription
with gentle.resampled(f) as wavfile:
aligner = gentle.ForcedAligner(resources, transcript)
result = aligner.transcribe(wavfile, progress_cb=on_progress, logging=logging)
# os.system('python align.py '+f+' words.txt -o test.json')
output = os.path.join('alignments', '/'.join(f.split('/')[-4:]).split('.')[0] + '.json')
pathlib.Path('/'.join(output.split('/')[0:-1])).mkdir(parents=True, exist_ok=True)
fh = open(output, 'w')
fh.write(result.to_json(indent=2))
if output:
logging.info("output written to %s" % (output))
fh.close()
data=load_emov_db(path)
align_db(data)
def get_start_end_from_json(path):
a=pd.read_json(os.path.join('file://localhost', os.path.abspath(path)))
b=pd.DataFrame.from_records(a.words)
print('start:')
start=b.start[0]
print(start)
print('end:')
end=b.end.round(2).tolist()[-1]
print(end)
return start, end
# path='alignments/EmoV-DB/bea/amused/amused_1-15_0001.json'
# start, end=get_start_end_from_json(path)
def play_start_end(path, start, end):
import sounddevice as sd
import librosa
y,fs=librosa.load(path)
sd.play(y[int(start*fs):int(end*fs)],fs)
def play(path):
import sounddevice as sd
import librosa
y,fs=librosa.load(path)
sd.play(y,fs) |