Datasets:
Tasks:
Automatic Speech Recognition
Sub-tasks:
keyword-spotting
Multilinguality:
multilingual
Size Categories:
10K<n<100K
ArXiv:
License:
File size: 5,903 Bytes
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# coding=utf-8
# Copyright 2022 The PolyAI and HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.
import csv
import os
import datasets
logger = datasets.logging.get_logger(__name__)
""" MInDS-14 Dataset"""
_CITATION = """\
@article{gerz2021multilingual,
title={Multilingual and cross-lingual intent detection from spoken data},
author={Gerz, Daniela and Su, Pei-Hao and Kusztos, Razvan and Mondal, Avishek and Lis, Michal and Singhal, Eshan and Mrk{\v{s}}i{\'c}, Nikola and Wen, Tsung-Hsien and Vuli{\'c}, Ivan},
journal={arXiv preprint arXiv:2104.08524},
year={2021}
}
"""
_DESCRIPTION = """\
MINDS-14 is training and evaluation resource for intent
detection task with spoken data. It covers 14
intents extracted from a commercial system
in the e-banking domain, associated with spoken examples in 14 diverse language varieties.
"""
_ALL_CONFIGS = sorted([
"cs-CZ", "de-DE", "en-AU", "en-GB", "en-US", "es-ES", "fr-FR", "it-IT", "ko-KR", "nl-NL", "pl-PL", "pt-PT", "ru-RU", "zh-CN"
])
_DESCRIPTION = "MINDS-14 is a dataset for the intent detection task with spoken data. It covers 14 intents extracted from a commercial system in the e-banking domain, associated with spoken examples in 14 diverse language varieties."
_HOMEPAGE_URL = "https://arxiv.org/abs/2104.08524"
_DATA_URL = "data/MInDS-14.zip"
class Minds14Config(datasets.BuilderConfig):
"""BuilderConfig for xtreme-s"""
def __init__(
self, name, description, homepage, data_url
):
super(Minds14Config, self).__init__(
name=self.name,
version=datasets.Version("1.0.0", ""),
description=self.description,
)
self.name = name
self.description = description
self.homepage = homepage
self.data_url = data_url
def _build_config(name):
return Minds14Config(
name=name,
description=_DESCRIPTION,
homepage=_HOMEPAGE_URL,
data_url=_DATA_URL,
)
class Minds14(datasets.GeneratorBasedBuilder):
DEFAULT_WRITER_BATCH_SIZE = 1000
BUILDER_CONFIGS = [_build_config(name) for name in _ALL_CONFIGS + ["all"]]
def _info(self):
task_templates = None
langs = _ALL_CONFIGS
features = datasets.Features(
{
"path": datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=8_000),
"transcription": datasets.Value("string"),
"english_transcription": datasets.Value("string"),
"intent_class": datasets.ClassLabel(
names=[
"abroad",
"address",
"app_error",
"atm_limit",
"balance",
"business_loan",
"card_issues",
"cash_deposit",
"direct_debit",
"freeze",
"high_value_payment",
"joint_account",
"latest_transactions",
"pay_bill",
]
),
"lang_id": datasets.ClassLabel(names=langs),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=("audio", "transcription"),
homepage=self.config.homepage,
citation=_CITATION,
task_templates=task_templates,
)
def _split_generators(self, dl_manager):
langs = (
_ALL_CONFIGS
if self.config.name == "all"
else [self.config.name]
)
archive_path = dl_manager.download_and_extract(self.config.data_url)
audio_path = dl_manager.extract(
os.path.join(archive_path, "MInDS-14", "audio.zip")
)
text_path = dl_manager.extract(
os.path.join(archive_path, "MInDS-14", "text.zip")
)
text_path = {l: os.path.join(text_path, f"{l}.csv") for l in langs}
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"audio_path": audio_path,
"text_paths": text_path,
},
)
]
def _generate_examples(self, audio_path, text_paths):
key = 0
for lang in text_paths.keys():
text_path = text_paths[lang]
with open(text_path, encoding="utf-8") as csv_file:
csv_reader = csv.reader(csv_file, delimiter=",", skipinitialspace=True)
next(csv_reader)
for row in csv_reader:
file_path, transcription, english_transcription, intent_class = row
file_path = os.path.join(audio_path, *file_path.split("/"))
yield key, {
"path": file_path,
"audio": file_path,
"transcription": transcription,
"english_transcription": english_transcription,
"intent_class": intent_class.lower(),
"lang_id": _ALL_CONFIGS.index(lang),
}
key += 1
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