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evi.py

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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 json
+import os
+
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+
+""" EVI Dataset"""
+
+_CITATION = """\
+@inproceedings{Spithourakis2022evi,
+    author      = {Georgios P. Spithourakis and Ivan Vuli\'{c} and Micha\l{} Lis and I\~{n}igo Casanueva and Pawe\l{} Budzianowski},
+    title       = {{EVI}: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification},
+    year        = {2022},
+    note        = {Data available at https://github.com/PolyAI-LDN/evi-paper},
+    url         = {https://arxiv.org/abs/2204.13496},
+    booktitle   = {Findings of NAACL (publication pending)}
+}
+"""  # noqa
+
+_ALL_CONFIGS = sorted([
+    "en-GB", "fr-FR", "pl-PL"
+])
+
+_DESCRIPTION = "EVI is a dataset for enrolment, identification, and verification"  # noqa
+
+_HOMEPAGE_URL = "https://arxiv.org/abs/2204.13496"
+
+_AUDIO_DATA_URL = "https://poly-public-data.s3.eu-west-2.amazonaws.com/evi-paper/audios.zip"  # noqa
+
+_VERSION = datasets.Version("0.0.4", "")
+
+
+class EviConfig(datasets.BuilderConfig):
+    """BuilderConfig for EVI"""
+
+    def __init__(
+        self, name, version, description, homepage, audio_data_url
+    ):
+        super().__init__(
+            name=self.name,
+            version=version,
+            description=self.description,
+        )
+        self.name = name
+        self.description = description
+        self.homepage = homepage
+        self.audio_data_url = audio_data_url
+
+
+def _build_config(name):
+    return EviConfig(
+        name=name,
+        version=_VERSION,
+        description=_DESCRIPTION,
+        homepage=_HOMEPAGE_URL,
+        audio_data_url=_AUDIO_DATA_URL,
+    )
+
+
+class Evi(datasets.GeneratorBasedBuilder):
+
+    DEFAULT_WRITER_BATCH_SIZE = 1000
+    BUILDER_CONFIGS = [
+        _build_config(name) for name in _ALL_CONFIGS
+    ]
+
+    def _info(self):
+        task_templates = None
+        langs = _ALL_CONFIGS
+        features = datasets.Features(
+            {
+                "lang_id": datasets.ClassLabel(names=langs),
+                "dialogue_id": datasets.Value("string"),
+                "speaker_id": datasets.Value("string"),
+                "turn_id": datasets.Value("int32"),
+                #
+                "target_profile_id": datasets.Value("string"),
+                #
+                "asr_transcription": datasets.Value("string"),
+                "asr_nbest": datasets.Sequence(datasets.Value("string")),
+                #
+                "path": datasets.Value("string"),
+                "audio": datasets.Audio(sampling_rate=8_000),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            version=self.config.version,
+            description=self.config.description,
+            homepage=self.config.homepage,
+            license="CC-BY-4.0",
+            citation=_CITATION,
+            features=features,
+            supervised_keys=None,
+            task_templates=task_templates,
+        )
+
+    def _split_generators(self, dl_manager):
+        langs = ([self.config.name])
+
+        audio_path = dl_manager.download_and_extract(
+            self.config.audio_data_url
+        )
+        text_path = ""
+        lang2text_path = {
+            _lang: os.path.join(
+                text_path,
+                f"dialogues.{_lang.split('-')[0]}.csv"
+            )
+            for _lang in langs
+        }
+        lang2audio_path = {
+            _lang: os.path.join(
+                audio_path,
+                f"{_lang.split('-')[0]}"
+            )
+            for _lang in langs
+        }
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "audio_paths": lang2audio_path,
+                    "text_paths": lang2text_path,
+                },
+            )
+        ]
+
+    def _generate_examples(self, audio_paths, text_paths):
+        key = 0
+        for lang in text_paths.keys():
+            text_path = text_paths[lang]
+            audio_path = audio_paths[lang]
+            with open(text_path, encoding="utf-8") as fin:
+                reader = csv.DictReader(
+                    fin, delimiter="\t", skipinitialspace=True
+                )
+                for dictrow in reader:
+                    dialogue_id = dictrow["dialogue_id"]
+                    turn_id = dictrow["turn_num"]
+                    file_path = os.path.join(
+                        audio_path,
+                        dialogue_id,
+                        f'{turn_id}.wav'
+                    )
+                    if not os.path.isfile(file_path):
+                        file_path = None
+                    example = {
+                        "lang_id": _ALL_CONFIGS.index(lang),
+                        "dialogue_id": dialogue_id,
+                        "speaker_id": dictrow["speaker_id"],
+                        "turn_id": turn_id,
+                        "target_profile_id": dictrow["scenario_id"],
+                        "asr_transcription": dictrow["transcription"],
+                        "asr_nbest": json.loads(dictrow["nbest"]),
+                        "path": file_path,
+                        "audio": file_path,
+                    }
+                    print(example)
+                    yield key, example
+                    key += 1