| import os |
| import datasets |
| import pandas as pd |
|
|
| _DESCRIPTION = """\ |
| This data is CS data |
| """ |
|
|
| _CITATION = "Some citation" |
|
|
| _data_dir = "data" |
|
|
| class CSData(datasets.GeneratorBasedBuilder): |
| |
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "path": datasets.Value("string"), |
| "filename": datasets.Audio(sampling_rate=16_000), |
| "transcription": datasets.Value("string"), |
| } |
| ), |
| supervised_keys=None, |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| download_dir = dl_manager.download_and_extract( |
| { |
| "files": os.path.join(_data_dir, "files.zip"), |
| "metadata": os.path.join(_data_dir, "metadata.zip") |
| } |
| ) |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={ |
| "split": datasets.Split.TRAIN, |
| "data_dir": os.path.join(download_dir["files"], "files"), |
| "metapath": os.path.join(download_dir["metadata"], "metadata", "data.csv"), |
| |
| }, |
| ), |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| ] |
|
|
| def _generate_examples(self, data_dir, metapath, split): |
| metadata = pd.read_csv(metapath) |
| for key, row in metadata.iterrows(): |
| audio_path = os.path.join(data_dir, row["filename"]) |
| yield key, { |
| "filename": audio_path, |
| "transcription": row["transcription"], |
| "path": audio_path, |
| } |
