import csv import datasets _PROMPTS_URLS = { "dev": "data/audios_dev_metadata.csv", } _ARCHIVES = { "dev": "data/dev.tar", } _PATH_TO_CLIPS = { "dev": "dev", } class NurcSPDataset(datasets.GeneratorBasedBuilder): def _info(self): return datasets.DatasetInfo( features=datasets.Features( { "audio_name": datasets.Value("string"), "file_path": datasets.Value("string"), "text": datasets.Value("string"), "start_time": datasets.Value("string"), "end_time": datasets.Value("string"), "duration": datasets.Value("string"), "quality": datasets.Value("string"), "speech_genre": datasets.Value("string"), "speech_style": datasets.Value("string"), "variety": datasets.Value("string"), "accent": datasets.Value("string"), "sex": datasets.Value("string"), "age_range": datasets.Value("string"), "num_speakers": datasets.Value("string"), "speaker_id": datasets.Value("string"), "audio": datasets.Audio(sampling_rate=16_000), } ) ) def _split_generators(self, dl_manager): prompts_path = dl_manager.download(_PROMPTS_URLS) archive = dl_manager.download(_ARCHIVES) return [ datasets.SplitGenerator( name = datasets.Split.VALIDATION, gen_kwargs = { "prompts_path": prompts_path["dev"], "path_to_clips": _PATH_TO_CLIPS["dev"], "audio_files": dl_manager.iter_archive(archive["dev"]), } ), ] def _generate_examples(self, prompts_path, path_to_clips, audio_files): examples = {} with open(prompts_path, "r") as f: csv_reader = csv.DictReader(f) for row in csv_reader: audio_name = row['audio_name'] file_path = row['file_path'] text = row['text'] start_time = row['start_time'] end_time = row['end_time'] duration = row['duration'] quality = row['quality'] speech_genre = row['speech_genre'] speech_style = row['speech_style'] variety = row['variety'] accent = row['accent'] sex = row['sex'] age_range = row['age_range'] num_speakers = row['num_speakers'] speaker_id = row['speaker_id'] examples[file_path] = { "audio_name": audio_name, "file_path": file_path, "text": text, "start_time": start_time, "end_time": end_time, "duration": duration, "quality": quality, "speech_genre": speech_genre, "speech_style": speech_style, "variety": variety, "accent": accent, "sex": sex, "age_range": age_range, "num_speakers": num_speakers, "speaker_id": speaker_id, } inside_clips_dir = False id_ = 0 for path, f in audio_files: if path.startswith(path_to_clips): inside_clips_dir = True if path in examples: audio = {"path": path, "bytes": f.read()} yield id_, {**examples[path], "audio": audio} id_ += 1 elif inside_clips_dir: break