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)