arctic-hs / arctic-hs.py
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# 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,
)
import pandas as pd
class ARCTICHSConfig(BuilderConfig):
def __init__(
self,
name,
**kwargs,
):
super(
ARCTICHSConfig,
self,
).__init__(
name=name,
**kwargs,
)
if self.name.endswith("_symmetric"):
self.is_symmetric = True
self.part = "_".join(self.name.split("_")[:-1])
else:
self.is_symmetric = False
self.part = self.name
class ARCTICHSDataset(GeneratorBasedBuilder):
DEFAULT_CONFIG_NAME = "cmu_us"
BUILDER_CONFIGS = [
ARCTICHSConfig(name=name)
for name in (
"cmu_non-us",
"cmu_us",
"l2",
"cmu_non-us_symmetric",
"cmu_us_symmetric",
"l2_symmetric",
)
]
def get_audio_archive_path(
self,
) -> Path:
return Path("data") / self.config.part / "splits" / f"test.tar.gz"
def get_metadata_paths(
self,
) -> Dict[str, Path]:
if self.config.part == "cmu_non-us":
return {
speaker: Path("data") / self.config.part / "pairs" / f"{speaker}.csv"
for speaker in (
"ahw",
"aup",
"awb",
"axb",
"fem",
"gka",
"jmk",
"ksp",
"rxr",
"slp",
)
}
elif self.config.part == "cmu_us":
return {
speaker: Path("data") / self.config.part / "pairs" / f"{speaker}.csv"
for speaker in (
"aew",
"bdl",
"clb",
"eey",
"ljm",
"lnh",
"rms",
"slt",
)
}
elif self.config.part == "l2":
return {
speaker: Path("data") / self.config.part / "pairs" / f"{speaker}.csv"
for speaker in (
"aba",
"asi",
"bwc",
"ebvs",
"erms",
"hjk",
"hkk",
"hqtv",
"lxc",
"mbmps",
"ncc",
"njs",
"pnv",
"rrbi",
"ska",
"svbi",
"thv",
"tlv",
"tni",
"txhc",
"ybaa",
"ydck",
"ykwk",
"zhaa",
)
}
def _info(self) -> DatasetInfo:
return DatasetInfo(
description="ARCTIC Human-Synthetic test dataset",
features=Features(
{
"audio": Audio(sampling_rate=16000),
"label": Value("string"),
}
),
supervised_keys=None,
homepage="https://huggingface.co/datasets/realnetworks-kontxt/arctic-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_iterable = self.get_audio_archive_path()
archive_iterable = download_manager.download(archive_iterable)
archive_iterable = download_manager.iter_archive(archive_iterable)
speaker_to_metadata_path = self.get_metadata_paths()
speaker_to_metadata_path = download_manager.download(speaker_to_metadata_path)
return [
SplitGenerator(
name=Split.TEST,
gen_kwargs={
"archive_iterable": archive_iterable,
"speaker_to_metadata_path": speaker_to_metadata_path,
},
),
]
def _generate_examples(
self,
archive_iterable: ArchiveIterable,
speaker_to_metadata_path: Dict[str, Path],
) -> Iterable[Tuple[int, Dict[str, Any]]]:
speaker_to_symmetric = dict()
for speaker, metadata_path in speaker_to_metadata_path.items():
df = pd.read_csv(metadata_path).astype(
{
"name": str,
"has_human_and_synthetic": bool,
}
)
symmetric_names = df[df["has_human_and_synthetic"]]["name"].tolist()
symmetric_names = set(symmetric_names)
if len(symmetric_names) != 0:
speaker_to_symmetric[speaker] = symmetric_names
current_index = 0
for audio_path, audio_file in archive_iterable:
path = Path(audio_path)
name = path.name
# Samples are located in one of 2 folders:
# - 'human'
# - 'synthetic`
#
# Therefore the label is the name of their parent folder
label = path.parent.name
speaker = path.parent.parent.name
if not self.config.is_symmetric or (
speaker in speaker_to_symmetric
and name in speaker_to_symmetric[speaker]
):
audio = {
"path": audio_path,
"bytes": audio_file.read(),
}
yield current_index, {
"audio": audio,
"label": label,
}
current_index += 1