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Computer Science > Computation and Language

arXiv:2204.08582 (cs)
[Submitted on 18 Apr 2022 (v1), last revised 17 Jun 2022 (this version, v2)]

Title:MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages

Authors:Jack FitzGerald, Christopher Hench, Charith Peris, Scott Mackie, Kay Rottmann, Ana Sanchez, Aaron Nash, Liam Urbach, Vishesh Kakarala, Richa Singh, Swetha Ranganath, Laurie Crist, Misha Britan, Wouter Leeuwis, Gokhan Tur, Prem Natarajan
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Abstract:We present the MASSIVE dataset--Multilingual Amazon Slu resource package (SLURP) for Slot-filling, Intent classification, and Virtual assistant Evaluation. MASSIVE contains 1M realistic, parallel, labeled virtual assistant utterances spanning 51 languages, 18 domains, 60 intents, and 55 slots. MASSIVE was created by tasking professional translators to localize the English-only SLURP dataset into 50 typologically diverse languages from 29 genera. We also present modeling results on XLM-R and mT5, including exact match accuracy, intent classification accuracy, and slot-filling F1 score. We have released our dataset, modeling code, and models publicly.
Comments: Preprint; 8 pages
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
Cite as: arXiv:2204.08582 [cs.CL]
  (or arXiv:2204.08582v2 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2204.08582

Submission history

From: Jack FitzGerald [view email]
[v1] Mon, 18 Apr 2022 22:40:52 UTC (950 KB)
[v2] Fri, 17 Jun 2022 17:19:15 UTC (411 KB)
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