| | from datasets import DatasetInfo, GeneratorBasedBuilder, Split, SplitGenerator, Value, Audio, Features |
| | import os |
| | import csv |
| |
|
| | class MyDataset(GeneratorBasedBuilder): |
| | def _info(self): |
| | return DatasetInfo( |
| | features=Features({ |
| | "audio": Audio(sampling_rate=16_000), |
| | "text": Value("string") |
| | }), |
| | ) |
| |
|
| | def _split_generators(self, dl_manager): |
| | audio_dir = os.path.join(self.config.data_dir, "audio") |
| | metadata_path = os.path.join(self.config.data_dir, "metadata.csv") |
| |
|
| | return [ |
| | SplitGenerator( |
| | name=Split.TRAIN, |
| | gen_kwargs={ |
| | "metadata_path": metadata_path, |
| | "audio_dir": audio_dir |
| | }, |
| | ) |
| | ] |
| |
|
| | def _generate_examples(self, metadata_path, audio_dir): |
| | with open(metadata_path, encoding="utf-8") as f: |
| | reader = csv.DictReader(f) |
| | for idx, row in enumerate(reader): |
| | yield idx, { |
| | "audio": os.path.join(audio_dir, row["file"]), |
| | "text": row["text"] |
| | } |