NURC-SP_ENTOA_TTS.py

import csv
import datasets
from datasets import BuilderConfig, GeneratorBasedBuilder, DatasetInfo, SplitGenerator, Split

_PROMPTS_URLS = {
    "dev": "automatic/validation.csv",
    "train": "automatic/train.csv",
}

_PROMPTS_FILTERED_URLS = {
    "dev": "automatic/validation.csv",
    "train": "automatic/train.csv",
}

_ARCHIVES = {
    "dev": "automatic.tar.gz",
    "train": "automatic.tar.gz",
}

_PATH_TO_CLIPS = {
    "dev": "validation",
    "train": "train",
}

class NurcSPConfig(BuilderConfig):
    def __init__(self, prompts_type="original", **kwargs):
        super().__init__(**kwargs)
        self.prompts_type = prompts_type

class NurcSPDataset(GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        NurcSPConfig(name="original", description="Original audio prompts", prompts_type="original"),
        NurcSPConfig(name="filtered", description="Filtered audio prompts", prompts_type="filtered"),
    ]

    def _info(self):
        return 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_urls = _PROMPTS_URLS if self.config.prompts_type == "original" else _PROMPTS_FILTERED_URLS
        
        # Download the prompts CSV files and audio archive
        prompts_path = dl_manager.download_and_extract(prompts_urls)
        archive = dl_manager.download_and_extract(_ARCHIVES)

        # Return split generators
        return [
            SplitGenerator(
                name=Split.TRAIN,
                gen_kwargs={
                    "prompts_path": prompts_path["train"],
                    "path_to_clips": _PATH_TO_CLIPS["train"],
                    "audio_files": archive["train"],
                }
            ),
            SplitGenerator(
                name=Split.VALIDATION,  # Changed from Split.VALIDATION to match error message
                gen_kwargs={
                    "prompts_path": prompts_path["dev"],
                    "path_to_clips": _PATH_TO_CLIPS["dev"],
                    "audio_files": archive["dev"],
                }
            ),
        ]

    def _generate_examples(self, prompts_path, path_to_clips, audio_files):
        # Load CSV data
        examples = {}
        with open(prompts_path, "r", encoding='utf-8') as f:
            csv_reader = csv.DictReader(f)
            for row in csv_reader:
                examples[row['file_path']] = {
                    key: row[key] 
                    for key in row.keys()
                }

        # Process audio files
        id_ = 0
        for root, _, files in datasets.utils.py_utils.walk(audio_files):
            if path_to_clips in root:
                for fname in files:
                    file_path = f"{path_to_clips}/{fname}"
                    if file_path in examples:
                        full_path = f"{root}/{fname}"
                        with open(full_path, "rb") as audio_file:
                            audio = {"path": file_path, "bytes": audio_file.read()}
                            yield id_, {**examples[file_path], "audio": audio}
                            id_ += 1