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| """MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages""" |
|
|
| import json |
| import datasets |
|
|
| logger = datasets.logging.get_logger(__name__) |
|
|
| _DESCRIPTION = """\ |
| MASSIVE is a parallel dataset of > 1M utterances across 51 languages with annotations |
| for the Natural Language Understanding tasks of intent prediction and slot annotation. |
| Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing |
| the SLURP dataset, composed of general Intelligent Voice Assistant single-shot interactions. |
| """ |
| _URL = "https://amazon-massive-nlu-dataset.s3.amazonaws.com/amazon-massive-dataset-1.0.tar.gz" |
|
|
| _LANGUAGES = [ |
| "af-ZA", |
| "am-ET", |
| "ar-SA", |
| "az-AZ", |
| "bn-BD", |
| "cy-GB", |
| "da-DK", |
| "de-DE", |
| "el-GR", |
| "en-US", |
| "es-ES", |
| "fa-IR", |
| "fi-FI", |
| "fr-FR", |
| "he-IL", |
| "hi-IN", |
| "hu-HU", |
| "hy-AM", |
| "id-ID", |
| "is-IS", |
| "it-IT", |
| "ja-JP", |
| "jv-ID", |
| "ka-GE", |
| "km-KH", |
| "kn-IN", |
| "ko-KR", |
| "lv-LV", |
| "ml-IN", |
| "mn-MN", |
| "ms-MY", |
| "my-MM", |
| "nb-NO", |
| "nl-NL", |
| "pl-PL", |
| "pt-PT", |
| "ro-RO", |
| "ru-RU", |
| "sl-SL", |
| "sq-AL", |
| "sv-SE", |
| "sw-KE", |
| "ta-IN", |
| "te-IN", |
| "th-TH", |
| "tl-PH", |
| "tr-TR", |
| "ur-PK", |
| "vi-VN", |
| "zh-CN", |
| "zh-TW", |
| ] |
|
|
| _SCENARIOS = [ |
| "social", |
| "transport", |
| "calendar", |
| "play", |
| "news", |
| "datetime", |
| "recommendation", |
| "email", |
| "iot", |
| "general", |
| "audio", |
| "lists", |
| "qa", |
| "cooking", |
| "takeaway", |
| "music", |
| "alarm", |
| "weather", |
| ] |
|
|
| _INTENTS = [ |
| "datetime_query", |
| "iot_hue_lightchange", |
| "transport_ticket", |
| "takeaway_query", |
| "qa_stock", |
| "general_greet", |
| "recommendation_events", |
| "music_dislikeness", |
| "iot_wemo_off", |
| "cooking_recipe", |
| "qa_currency", |
| "transport_traffic", |
| "general_quirky", |
| "weather_query", |
| "audio_volume_up", |
| "email_addcontact", |
| "takeaway_order", |
| "email_querycontact", |
| "iot_hue_lightup", |
| "recommendation_locations", |
| "play_audiobook", |
| "lists_createoradd", |
| "news_query", |
| "alarm_query", |
| "iot_wemo_on", |
| "general_joke", |
| "qa_definition", |
| "social_query", |
| "music_settings", |
| "audio_volume_other", |
| "calendar_remove", |
| "iot_hue_lightdim", |
| "calendar_query", |
| "email_sendemail", |
| "iot_cleaning", |
| "audio_volume_down", |
| "play_radio", |
| "cooking_query", |
| "datetime_convert", |
| "qa_maths", |
| "iot_hue_lightoff", |
| "iot_hue_lighton", |
| "transport_query", |
| "music_likeness", |
| "email_query", |
| "play_music", |
| "audio_volume_mute", |
| "social_post", |
| "alarm_set", |
| "qa_factoid", |
| "calendar_set", |
| "play_game", |
| "alarm_remove", |
| "lists_remove", |
| "transport_taxi", |
| "recommendation_movies", |
| "iot_coffee", |
| "music_query", |
| "play_podcasts", |
| "lists_query", |
| ] |
|
|
|
|
| class MASSIVE(datasets.GeneratorBasedBuilder): |
| """MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages""" |
|
|
| BUILDER_CONFIGS = [ |
| datasets.BuilderConfig( |
| name=name, |
| version=datasets.Version("1.0.0"), |
| description=f"The MASSIVE corpora for {name}", |
| ) |
| for name in _LANGUAGES |
| ] |
|
|
| DEFAULT_CONFIG_NAME = "en-US" |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "id": datasets.Value("string"), |
| "locale": datasets.Value("string"), |
| "partition": datasets.Value("string"), |
| "scenario": datasets.features.ClassLabel(names=_SCENARIOS), |
| "intent": datasets.features.ClassLabel(names=_INTENTS), |
| "utt": datasets.Value("string"), |
| "annot_utt": datasets.Value("string"), |
| "worker_id": datasets.Value("string"), |
| "slot_method": datasets.Sequence( |
| { |
| "slot": datasets.Value("string"), |
| "method": datasets.Value("string"), |
| } |
| ), |
| "judgments": datasets.Sequence( |
| { |
| "worker_id": datasets.Value("string"), |
| "intent_score": datasets.Value("int8"), |
| "slots_score": datasets.Value("int8"), |
| "grammar_score": datasets.Value("int8"), |
| "spelling_score": datasets.Value("int8"), |
| "language_identification": datasets.Value("string"), |
| } |
| ), |
| }, |
| ), |
| supervised_keys=None, |
| homepage="https://github.com/alexa/massive", |
| citation="_CITATION", |
| license="_LICENSE", |
| ) |
|
|
| def _split_generators(self, dl_manager): |
|
|
| path = dl_manager.iter_archive(_URL) |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={ |
| "filepath": path, |
| "split": "train", |
| "lang": self.config.name, |
| }, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.VALIDATION, |
| gen_kwargs={ |
| "filepath": path, |
| "split": "dev", |
| "lang": self.config.name, |
| }, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.TEST, |
| gen_kwargs={ |
| "filepath": path, |
| "split": "test", |
| "lang": self.config.name, |
| }, |
| ), |
| ] |
|
|
| def _generate_examples(self, filepath, split, lang): |
|
|
| filepath = filepath + "/1.0/data/" + lang + ".jsonl" |
|
|
| logger.info("⏳ Generating examples from = %s", filepath) |
|
|
| |
| f = open(filepath, "r") |
| lines = f.read().split("\n") |
| f.close() |
|
|
| key_ = 0 |
|
|
| for line in lines: |
|
|
| data = json.loads(line) |
|
|
| if data["partition"] != split: |
| continue |
|
|
| |
| if "slot_method" in data: |
| slot_method = [ |
| { |
| "slot": s["slot"], |
| "method": s["method"], |
| } |
| for s in data["slot_method"] |
| ] |
| else: |
| slot_method = [] |
|
|
| |
| if "judgments" in data: |
| judgments = [ |
| { |
| "worker_id": j["worker_id"], |
| "intent_score": j["intent_score"], |
| "slots_score": j["slots_score"], |
| "grammar_score": j["grammar_score"], |
| "spelling_score": j["spelling_score"], |
| "language_identification": j["language_identification"], |
| } |
| for j in data["judgments"] |
| ] |
| else: |
| judgments = [] |
|
|
| yield key_, { |
| "id": data["id"], |
| "locale": data["locale"], |
| "partition": data["partition"], |
| "scenario": data["scenario"], |
| "intent": data["intent"], |
| "utt": data["utt"], |
| "annot_utt": data["annot_utt"], |
| "worker_id": data["worker_id"], |
| "slot_method": slot_method, |
| "judgments": judgments, |
| } |
|
|
| key_ += 1 |
|
|
