MOCKS.py

# coding=utf-8
# Copyright 2023 The HuggingFace Datasets Authors.
#
# Licensed under the Creative Commons version 4.0 and Mozilla Public License version 2.0,
# (the "Licenses"); you may not use this file except in compliance with the Licenses.
# You may obtain a copies of the Licenses at
#
#     https://creativecommons.org/licenses/by/4.0/
#     and https://www.mozilla.org/en-US/MPL/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 Licenses for the specific language governing permissions and
# limitations under the Licenses.

# Lint as: python3

import csv
import os

import datasets


logger = datasets.logging.get_logger(__name__)


_CITATION = """\
@inproceedings{pudo23_interspeech,
  author={Mikołaj Pudo and Mateusz Wosik and Adam Cieślak and Justyna Krzywdziak and Bożena Łukasiak and Artur Janicki},
  title={{MOCKS} 1.0: Multilingual Open Custom Keyword Spotting Testset},
  year={2023},
  booktitle={Proc. Interspeech 2023},
}
"""

_DESCRIPTION = """\
Multilingual Open Custom Keyword Spotting Testset (MOCKS) is a comprehensive 
audio testset for evaluation and benchmarking Open-Vocabulary Keyword Spotting (OV-KWS) models.
"""


_BASE_URL = "https://huggingface.co/datasets/voiceintelligenceresearch/MOCKS/tree/main"
_DL_URLS = {
    "de.MCV": {
        "offline": "de/MCV/test/offline/data.tar.gz",
        "online": "de/MCV/test/online/data.tar.gz",
        "offline_transcription" : "de/MCV/test/data_offline_transcription.tsv",
        "online_transcription" : "de/MCV/test/data_online_transcription.tsv",
    },
    "en.LS-clean": {
        "offline": "en/LS-clean/test/offline/data.tar.gz",
        "online": "en/LS-clean/test/online/data.tar.gz",
        "offline_transcription" : "en/LS-clean/test/data_offline_transcription.tsv",
        "online_transcription" : "en/LS-clean/test/data_online_transcription.tsv",
    },
    "en.LS-other": {
        "offline": "en/LS-other/test/offline/data.tar.gz",
        "online": "en/LS-other/test/online/data.tar.gz",
        "offline_transcription" : "en/LS-other/test/data_offline_transcription.tsv",
        "online_transcription" : "en/LS-other/test/data_online_transcription.tsv",
    },
    "en.MCV": {
        "offline": "en/MCV/test/offline/data.tar.gz",
        "online": "en/MCV/test/online/data.tar.gz",
        "offline_transcription" : "en/MCV/test/data_offline_transcription.tsv",
        "online_transcription" : "en/MCV/test/data_online_transcription.tsv",
    },
    "es.MCV": {
        "offline": "es/MCV/test/offline/data.tar.gz",
        "online": "es/MCV/test/online/data.tar.gz",
        "offline_transcription" : "es/MCV/test/data_offline_transcription.tsv",
        "online_transcription" : "es/MCV/test/data_online_transcription.tsv",
    },
    "fr.MCV": {
        "offline": "fr/MCV/test/offline/data.tar.gz",
        "online": "fr/MCV/test/online/data.tar.gz",
        "offline_transcription": "fr/MCV/test/data_offline_transcription.tsv",
        "online_transcription": "fr/MCV/test/data_online_transcription.tsv",
    },
    "it.MCV": {
        "offline": "it/MCV/test/offline/data.tar.gz",
        "online": "it/MCV/test/online/data.tar.gz",
        "offline_transcription": "it/MCV/test/data_offline_transcription.tsv",
        "online_transcription": "it/MCV/test/data_online_transcription.tsv",
    },
    "all": {
        "de.MCV.offline": "de/MCV/test/offline/data.tar.gz",
        "de.MCV.online": "de/MCV/test/online/data.tar.gz",
        "en.LS-clean.offline": "en/LS-clean/test/offline/data.tar.gz",
        "en.LS-clean.online": "en/LS-clean/test/online/data.tar.gz",
        "en.LS-other.offline": "en/LS-other/test/offline/data.tar.gz",
        "en.LS-other.online": "en/LS-other/test/online/data.tar.gz",
        "en.MCV.offline": "en/MCV/test/offline/data.tar.gz",
        "en.MCV.online": "en/MCV/test/online/data.tar.gz",
        "es.MCV.offline": "es/MCV/test/offline/data.tar.gz",
        "es.MCV.online": "es/MCV/test/online/data.tar.gz",
        "fr.MCV.offline": "fr/MCV/test/offline/data.tar.gz",
        "fr.MCV.online": "fr/MCV/test/online/data.tar.gz",
        "it.MCVoffline": "it/MCV/test/offline/data.tar.gz",
        "it.MCV.online": "it/MCV/test/online/data.tar.gz",
        "de.MCV.offline_transcription": "de/MCV/test/data_offline_transcription.tsv",
        "de.MCV.online_transcription": "de/MCV/test/data_online_transcription.tsv",
        "en.LS-clean.offline_transcription": "en/LS-clean/test/data_offline_transcription.tsv",
        "en.LS-clean.online_transcription": "en/LS-clean/test/data_online_transcription.tsv",
        "en.LS-other.offline_transcription": "en/LS-other/test/data_offline_transcription.tsv",
        "en.LS-other.online_transcription": "en/LS-other/test/data_online_transcription.tsv",
        "en.MCV.offline_transcription": "en/MCV/test/data_offline_transcription.tsv",
        "en.MCVonline_transcription": "en/MCV/test/data_online_transcription.tsv",
        "es.MCV.offline_transcription": "es/MCV/test/data_offline_transcription.tsv",
        "es.MCV.online_transcription": "es/MCV/test/data_online_transcription.tsv",
        "fr.MCV.offline_transcription": "fr/MCV/test/data_offline_transcription.tsv",
        "fr.MCV.online_transcription": "fr/MCV/test/data_online_transcription.tsv",
        "it.MCV.offline_transcription": "it/MCV/test/data_offline_transcription.tsv",
        "it.MCV.online_transcription": "it/MCV/test/data_online_transcription.tsv",
    }
}


class Mocks(datasets.GeneratorBasedBuilder):
    """Mocks Dataset."""
    DEFAULT_CONFIG_NAME = "all"

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="de.MCV", description="German Mozilla Common Voice."),
        datasets.BuilderConfig(name="en.LS-clean", description="English LibriSpeech 'Clean'."),
        datasets.BuilderConfig(name="en.LS-other", description="English LibriSpeech 'Other'."),
        datasets.BuilderConfig(name="en.MCV", description="English Mozilla Common Voice."),
        datasets.BuilderConfig(name="es.MCV", description="Spanish Mozilla Common Voice."),
        datasets.BuilderConfig(name="fr.MCV", description="French Mozilla Common Voice."),
        datasets.BuilderConfig(name="it.MCV", description="Italian Mozilla Common Voice."),
        datasets.BuilderConfig(name="all", description="All test set."),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "audio_id": datasets.Value("string"),
                    "audio": datasets.Audio(sampling_rate=16_000),
                    "transcription": datasets.Value("string"),
                }
            ),
            homepage=_BASE_URL,
            citation=_CITATION
        )

    def _split_generators(self, dl_manager):
        archive_path = dl_manager.download(_DL_URLS[self.config.name])

        if self.config.name == "de.MCV":
            offline_split = [
                datasets.SplitGenerator(
                    name="offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["offline"]),
                        "transcription": archive_path["offline_transcription"],
                        "s_type": "offline"
                    }
                )
            ]
            online_split = [
                datasets.SplitGenerator(
                    name="online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["online"]),
                        "transcription": archive_path["online_transcription"],
                        "s_type": "online"
                    }
                )
            ]

        elif self.config.name == "en.LS-clean":
            offline_split = [
                datasets.SplitGenerator(
                    name="offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["offline"]),
                        "transcription": archive_path["offline_transcription"],
                        "s_type": "offline"
                    }
                )
            ]
            online_split = [
                datasets.SplitGenerator(
                    name="online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["online"]),
                        "transcription": archive_path["online_transcription"],
                        "s_type": "online"
                    }
                )
            ]

        elif self.config.name == "en.LS-other":
            offline_split = [
                datasets.SplitGenerator(
                    name="offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["offline"]),
                        "transcription": archive_path["offline_transcription"],
                        "s_type": "offline"
                    }
                )
            ]
            online_split = [
                datasets.SplitGenerator(
                    name="online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["online"]),
                        "transcription": archive_path["online_transcription"],
                        "s_type": "online"
                    }
                )
            ]        

        elif self.config.name == "en.MCV":
            offline_split = [
                datasets.SplitGenerator(
                    name="offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["offline"]),
                        "transcription": archive_path["offline_transcription"],
                        "s_type": "offline"
                    }
                )
            ]
            online_split = [
                datasets.SplitGenerator(
                    name="online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["online"]),
                        "transcription": archive_path["online_transcription"],
                        "s_type": "online"
                    }
                )
            ]

        elif self.config.name == "es.MCV":
            offline_split = [
                datasets.SplitGenerator(
                    name="offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["offline"]),
                        "transcription": archive_path["offline_transcription"],
                        "s_type": "offline"
                    }
                )
            ]
            online_split = [
                datasets.SplitGenerator(
                    name="online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["online"]),
                        "transcription": archive_path["online_transcription"],
                        "s_type": "online"
                    }
                )
            ]
        
        elif self.config.name == "fr.MCV":
            offline_split = [
                datasets.SplitGenerator(
                    name="offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["offline"]),
                        "transcription": archive_path["offline_transcription"],
                        "s_type": "offline"
                    }
                )
            ]
            online_split = [
                datasets.SplitGenerator(
                    name="online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["online"]),
                        "transcription": archive_path["online_transcription"],
                        "s_type": "online"
                    }
                )
            ]

        elif self.config.name == "it.MCV":
            offline_split = [
                datasets.SplitGenerator(
                    name="offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["offline"]),
                        "transcription": archive_path["offline_transcription"],
                        "s_type": "offline"
                    }
                )
            ]
            online_split = [
                datasets.SplitGenerator(
                    name="online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["online"]),
                        "transcription": archive_path["online_transcription"],
                        "s_type": "online"
                    }
                )
            ]

        elif self.config.name == "all": 
            offline_split = [
                datasets.SplitGenerator(
                    name="de.MCV.offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["de.MCV.offline"]),
                        "transcription": archive_path["de.MCV.offline_transcription"],
                        "s_type": "offline"
                    }
                ),
                datasets.SplitGenerator(
                    name="en.LS-clean.offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["en.LS-clean.offline"]),
                        "transcription": archive_path["en.LS-clean.offline_transcription"],
                        "s_type": "offline"
                    }
                ),
                datasets.SplitGenerator(
                    name="en.LS-other.offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["en.LS-other.offline"]),
                        "transcription": archive_path["en.LS-other.offline_transcription"],
                        "s_type": "offline"
                    }
                ),
                datasets.SplitGenerator(
                    name="en.MCV.offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["en.MCV.offline"]),
                        "transcription": archive_path["en.MCV.offline_transcription"],
                        "s_type": "offline"
                    }
                ),
                datasets.SplitGenerator(
                    name="es.MCV.offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["es.MCV.offline"]),
                        "transcription": archive_path["es.MCV.offline_transcription"],
                        "s_type": "offline"
                    }
                ),
                datasets.SplitGenerator(
                    name="fr.MCV.offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["fr.MCV.offline"]),
                        "transcription": archive_path["fr.MCV.offline_transcription"],
                        "s_type": "offline"
                    }
                ),
                datasets.SplitGenerator(
                    name="it.MCV.offline",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["it.MCV.offline"]),
                        "transcription": archive_path["it.MCV.offline_transcription"],
                        "s_type": "offline"
                    }
                )
            ]
            online_split = [
                datasets.SplitGenerator(
                    name="de.MCV.online",
                    gen_kwargs={
                        "transcription": archive_path["de.MCV.offline_transconline"],
                        "s_type": "online"
                    }
                ),
                datasets.SplitGenerator(
                    name="en.LS-clean.online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["en.LS-clean.online"]),
                        "transcription": archive_path["en.LS-clean.online_transcription"],
                        "s_type": "online"
                    }
                ),
                datasets.SplitGenerator(
                    name="en.LS-other.online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["en.LS-other.online"]),
                        "transcription": archive_path["en.LS-other.online_transcription"],
                        "s_type": "online"
                    }
                ),
                datasets.SplitGenerator(
                    name="en.MCV.online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["en.MCV.online"]),
                        "transcription": archive_path["en.MCV.online_transcription"],
                        "s_type": "online"
                    }
                ),
                datasets.SplitGenerator(
                    name="es.MCV.online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["es.MCV.online"]),
                        "transcription": archive_path["es.MCV.online_transcription"],
                        "s_type": "online"
                    }
                ),
                datasets.SplitGenerator(
                    name="fr.MCV.online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["fr.MCV.online"]),
                        "transcription": archive_path["fr.MCV.online_transcription"],
                        "s_type": "online"
                    }
                ),
                datasets.SplitGenerator(
                    name="it.MCV.online",
                    gen_kwargs={
                        "audio_files": dl_manager.iter_archive(archive_path["it.MCV.online"]),
                        "transcription": archive_path["it.MCV.online_transcription"],
                        "s_type": "online"
                    }
                )
            ]

        return online_split + offline_split

    def _generate_examples(self, audio_files, transcription, s_type):
        """Lorem ipsum."""
        metadata = {}
        with open(transcription, encoding="utf-8") as f:
            f = csv.reader(f, delimiter="\t")
            for row in f:
                audio_id = row[0].split("/")[-1]
                keyword_transcription = row[1]
                metadata[audio_id] = {"audio_id": audio_id, "transcription": keyword_transcription}

        id_ = 0
        for path, f in audio_files:
            _, audio_name = os.path.split(path)
            if audio_name in metadata:
                audio = {"bytes": f.read()}
                yield id_, {**metadata[audio_name], "audio": audio}
                id_ +=1