Datasets:

PolyAI
/

minds14

	# 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