title: Speech-MASSIVE: A Multilingual Speech Dataset for SLU and Beyond
summary: We present Speech-MASSIVE, a multilingual Spoken Language Understanding (SLU)
  dataset comprising the speech counterpart for a portion of the MASSIVE textual
  corpus. Speech-MASSIVE covers 12 languages from different families and inherits
  from MASSIVE the annotations for the intent prediction and slot-filling tasks.
  Our extension is prompted by the scarcity of massively multilingual SLU
  datasets and the growing need for versatile speech datasets to assess
  foundation models (LLMs, speech encoders) across languages and tasks. We
  provide a multimodal, multitask, multilingual dataset and report SLU baselines
  using both cascaded and end-to-end architectures in various training scenarios
  (zero-shot, few-shot, and full fine-tune). Furthermore, we demonstrate the
  suitability of Speech-MASSIVE for benchmarking other tasks such as speech
  transcription, language identification, and speech translation. The dataset,
  models, and code are publicly available at:
  https://github.com/hlt-mt/Speech-MASSIVE
paper_authors._id: 66b42911b9034abdbf691d00
paper_authors.name: Beomseok Lee
paper_authors.status: admin_assigned
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paper_authors.fullname: Beomseok LEE
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paper_authors.user: Beomseok-LEE
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paper_authors.name: Ioan Calapodescu
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paper_authors.fullname: Ioan Calapodescu
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paper_authors.user: ioan-calapodescu
paper_authors._id: 66b42911b9034abdbf691d02
paper_authors.name: Marco Gaido
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paper_authors.fullname: Marco Gaido
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paper_authors.user: mgaido91
paper_authors._id: 66b42911b9034abdbf691d03
paper_authors.name: Matteo Negri
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paper_authors.fullname: Matteo Negri
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paper_authors.user: MNegri
paper_authors._id: 66b42911b9034abdbf691d04
paper_authors.name: Laurent Besacier
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-08-08T10:55:39.913Z
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paper_authors.fullname: laurent besacier
paper_authors.type: user
paper_authors.user: besacier
paper_title: Speech-MASSIVE: A Multilingual Speech Dataset for SLU and Beyond
paper_summary: We present Speech-MASSIVE, a multilingual Spoken Language Understanding (SLU)
  dataset comprising the speech counterpart for a portion of the MASSIVE textual
  corpus. Speech-MASSIVE covers 12 languages from different families and inherits
  from MASSIVE the annotations for the intent prediction and slot-filling tasks.
  Our extension is prompted by the scarcity of massively multilingual SLU
  datasets and the growing need for versatile speech datasets to assess
  foundation models (LLMs, speech encoders) across languages and tasks. We
  provide a multimodal, multitask, multilingual dataset and report SLU baselines
  using both cascaded and end-to-end architectures in various training scenarios
  (zero-shot, few-shot, and full fine-tune). Furthermore, we demonstrate the
  suitability of Speech-MASSIVE for benchmarking other tasks such as speech
  transcription, language identification, and speech translation. The dataset,
  models, and code are publicly available at:
  https://github.com/hlt-mt/Speech-MASSIVE
paper_ai_keywords: multilingual Spoken Language Understanding (SLU) speech counterpart text corpus intent prediction slot-filling tasks cascaded architectures end-to-end architectures zero-shot few-shot full fine-tune benchmarking speech translation