import os import datasets logger = datasets.logging.get_logger(__name__) datasets.logging.set_verbosity(20) _speaker_names = [ 'ariana_Male2', 'moujeze_Female1', 'ariana_Male1', 'ariana_Female1' ] class ParsiGoo(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("1.0.0") def _info(self): features = datasets.Features( { "text": datasets.Value("string"), "audio_file": datasets.Value("string"), "speaker_name": datasets.Value("string"), "root_path": datasets.Value("string") } ) return datasets.DatasetInfo( description="ParsiGoo dataset", features=features, homepage="https://example.com", citation="", ) def _split_generators(self, dl_manager): logger.info("| > ") print("4544444") print(dl_manager.manual_dir) # logger.info(os.path.join(os.path.dirname(os.path.abspath(__file__)), "datasets")) data_dir = dl_manager.download_and_extract("https://huggingface.co/datasets/Kamtera/ParsiGoo/resolve/main/datasets.zip") # data_dir="datasets" data_dir = os.path.join(data_dir, "datasets") print("| > data_dir =",data_dir) meta_files = [] speaker_names = _speaker_names root_path = "" print("| > listdir =",os.listdir(data_dir)) for speaker_name in os.listdir(data_dir): # if not os.path.isdir(os.path.join(data_dir, speaker_name)): # continue root_path = os.path.join(data_dir, speaker_name) meta_files.append(os.path.join(root_path, "metadata.csv")) return [datasets.SplitGenerator( name="train", gen_kwargs={ "txt_files": meta_files, "speaker_names": speaker_names, "root_path": root_path } )] def _generate_examples(self, txt_files, speaker_names, root_path): print(txt_files) id=-1 for ind,txt_file in enumerate(txt_files): with open(txt_file, "r", encoding="utf-8") as ttf: for i, line in enumerate(ttf): cols = line.split("|") wav_file = cols[1].strip() text = cols[0].strip() wav_file = os.path.join(root_path, "wavs", wav_file) id+=1 yield id, {"text": text, "audio_file": wav_file, "speaker_name": speaker_names[ind], "root_path": root_path}