kscg_small_20v50_16k.py

import datasets

_DATA_URL = "data/kscg_small_20v50_16k.tar.gz"

_PROMPTS_URLS = {
    "train": "data/prompts-train.txt.gz",
    "test": "data/prompts-test.txt.gz",
}

class KscgSmall25(datasets.GeneratorBasedBuilder):
    """KSCG Small 20v50"""

    def _info(self):
        features = datasets.Features(
            {
                'path': datasets.Value('string'),
                'audio': datasets.Audio(sampling_rate=16_000),
                'gender': datasets.ClassLabel(
                    num_classes=2,
                    names=[
                        'M',
                        'F',
                    ]
                ),
                'age': datasets.ClassLabel(
                    num_classes=2,
                    names=[
                        '20s',
                        '50s'
                    ]
                )
            }
        )

        return datasets.DatasetInfo(
            features=features,
            supervised_keys=None,
        )
    
    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""

        prompts_paths = dl_manager.download_and_extract(_PROMPTS_URLS)
        archive = dl_manager.download(_DATA_URL)
        train_dir = "kscg_small_20v50/train"
        test_dir = "kscg_small_20v50/test"

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "prompts_path": prompts_paths["train"],
                    "path_to_clips": train_dir,
                    "audio_files": dl_manager.iter_archive(archive)
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "prompts_path": prompts_paths["test"],
                    "path_to_clips": test_dir,
                    "audio_files": dl_manager.iter_archive(archive)
                },
            ),            
        ]
    
    def _generate_examples(self, prompts_path, path_to_clips, audio_files):
        examples = {}
        with open(prompts_path, encoding='utf-8') as f:
            for row in f:
                data = row.strip().split(",")
                audio_path = data[0] + ".wav"
                examples[audio_path] = {
                    'path': audio_path,
                    # 'phone_transcription': data[1],
                    'gender': data[1],
                    'age': data[2]
                }
        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