# Copyright 2024 RealNetworks # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from pathlib import Path from typing import ( Any, Dict, Iterable, List, Tuple, ) from datasets import ( Audio, BuilderConfig, DatasetInfo, Features, GeneratorBasedBuilder, Split, SplitGenerator, Value, ) from datasets.download.download_manager import ( ArchiveIterable, DownloadManager, ) class FLEURSHSConfig(BuilderConfig): def __init__( self, name, **kwargs, ): super( FLEURSHSConfig, self, ).__init__( name=name, **kwargs, ) class FLEURSHSDataset(GeneratorBasedBuilder): DEFAULT_CONFIG_NAME = "en_us" BUILDER_CONFIGS = [ FLEURSHSConfig(name=name) for name in ( "de_de", "en_us", "es_419", "fr_fr", "it_it", "nl_nl", "pl_pl", "sv_se", ) ] def get_audio_archive_path( self, split: str, ) -> Path: return Path("data") / self.config.name / "splits" / f"{split}.tar.gz" def _info(self) -> DatasetInfo: return DatasetInfo( description="FLEURS Human-Synthetic classification dataset", features=Features( { "audio": Audio(sampling_rate=16000), "label": Value("string"), } ), supervised_keys=None, homepage="https://huggingface.co/datasets/realnetworks-kontxt/fleurs-hs", license="CC BY 4.0", citation="\n".join( ( "@inproceedings{dropuljic-ssdww2v2ivls", "author={Dropuljić, Branimir and Šuflaj, Miljenko and Jertec, Andrej and Obadić, Leo}", "booktitle={2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)}", "title={Synthetic speech detection with Wav2Vec 2.0 in various language settings}", "year={2024}", "volume={}", "number={}", "pages={1-5}", "keywords={Synthetic speech detection;text-to-speech;wav2vec 2.0;spoofing attack;multilingualism}", "doi={}", # TODO: Add DOI once known "}", ) ), ) def _split_generators( self, download_manager: DownloadManager, ) -> List[SplitGenerator]: archive_iterables = { split: str(self.get_audio_archive_path(split=split)) for split in ( "train", "dev", "test", ) } archive_iterables = download_manager.download(archive_iterables) archive_iterables = { split: download_manager.iter_archive(path) for split, path in archive_iterables.items() } return [ SplitGenerator( name=Split.TRAIN, gen_kwargs={ "archive_iterable": archive_iterables["train"], }, ), SplitGenerator( name=Split.VALIDATION, gen_kwargs={ "archive_iterable": archive_iterables["dev"], }, ), SplitGenerator( name=Split.TEST, gen_kwargs={ "archive_iterable": archive_iterables["test"], }, ), ] def _generate_examples( self, archive_iterable: ArchiveIterable, ) -> Iterable[Tuple[int, Dict[str, Any]]]: current_index = 0 for audio_path, audio_file in archive_iterable: audio = { "path": audio_path, "bytes": audio_file.read(), } # Samples are located in one of 2 folders: # - 'human' # - 'synthetic` # # Therefore the label is the name of their parent folder label = Path(audio_path).parent.name yield current_index, { "audio": audio, "label": label, } current_index += 1