Speech-MASSIVE: A Multilingual Speech Dataset for SLU and Beyond
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
66b42911b9034abdbf691d00
Beomseok Lee
admin_assigned
2024-08-08T10:55:15.035Z
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Beomseok LEE
user
Beomseok-LEE
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Ioan Calapodescu
admin_assigned
2024-08-08T10:55:20.840Z
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Ioan Calapodescu
user
ioan-calapodescu
66b42911b9034abdbf691d02
Marco Gaido
admin_assigned
2024-08-08T10:55:26.335Z
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Marco Gaido
user
mgaido91
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Matteo Negri
admin_assigned
2024-08-08T10:55:34.441Z
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/avatars/1ad7aa4e8e6d80c5d50bf4de502f11a4.svg
Matteo Negri
user
MNegri
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Laurent Besacier
admin_assigned
2024-08-08T10:55:39.913Z
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laurent besacier
user
besacier
Speech-MASSIVE: A Multilingual Speech Dataset for SLU and Beyond
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
A multilingual spoken language understanding dataset developed for evaluating foundation models across languages and tasks, offering scenarios for zero-shot, few-shot, and full fine-tuning.
spoken language understanding multilingual dataset intent prediction slot-filling foundation models cascaded architectures end-to-end architectures zero-shot few-shot full fine-tune speech transcription language identification speech translation