Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti

Fardin Ahsan Sakib; A H M Rezaul Karim; Saadat Hasan Khan; Md Mushfiqur Rahman

doi:10.18653/v1/2023.banglalp-1.6

Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti

Fardin Ahsan Sakib, A H M Rezaul Karim, Saadat Hasan Khan, Md Mushfiqur Rahman

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Abstract

As voice assistants cement their place in our technologically advanced society, there remains a need to cater to the diverse linguistic landscape, including colloquial forms of low-resource languages. Our study introduces the first-ever comprehensive dataset for intent detection and slot filling in formal Bangla, colloquial Bangla, and Sylheti languages, totaling 984 samples across 10 unique intents. Our analysis reveals the robustness of large language models for tackling downstream tasks with inadequate data. The GPT-3.5 model achieves an impressive F1 score of 0.94 in intent detection and 0.51 in slot filling for colloquial Bangla.

Anthology ID:: 2023.banglalp-1.6
Volume:: Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)
Month:: December
Year:: 2023
Address:: Singapore
Editors:: Firoj Alam, Sudipta Kar, Shammur Absar Chowdhury, Farig Sadeque, Ruhul Amin
Venue:: BanglaLP
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 48–55
Language:
URL:: https://aclanthology.org/2023.banglalp-1.6/
DOI:: 10.18653/v1/2023.banglalp-1.6
Bibkey:
Cite (ACL):: Fardin Ahsan Sakib, A H M Rezaul Karim, Saadat Hasan Khan, and Md Mushfiqur Rahman. 2023. Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti. In Proceedings of the First Workshop on Bangla Language Processing (BLP-2023), pages 48–55, Singapore. Association for Computational Linguistics.
Cite (Informal):: Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti (Sakib et al., BanglaLP 2023)
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PDF:: https://aclanthology.org/2023.banglalp-1.6.pdf

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@inproceedings{sakib-etal-2023-intent,
    title = "Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for {B}angla and {S}ylheti",
    author = "Sakib, Fardin Ahsan  and
      Karim, A H M Rezaul  and
      Khan, Saadat Hasan  and
      Rahman, Md Mushfiqur",
    editor = "Alam, Firoj  and
      Kar, Sudipta  and
      Chowdhury, Shammur Absar  and
      Sadeque, Farig  and
      Amin, Ruhul",
    booktitle = "Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.banglalp-1.6/",
    doi = "10.18653/v1/2023.banglalp-1.6",
    pages = "48--55",
    abstract = "As voice assistants cement their place in our technologically advanced society, there remains a need to cater to the diverse linguistic landscape, including colloquial forms of low-resource languages. Our study introduces the first-ever comprehensive dataset for intent detection and slot filling in formal Bangla, colloquial Bangla, and Sylheti languages, totaling 984 samples across 10 unique intents. Our analysis reveals the robustness of large language models for tackling downstream tasks with inadequate data. The GPT-3.5 model achieves an impressive F1 score of 0.94 in intent detection and 0.51 in slot filling for colloquial Bangla."
}

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%0 Conference Proceedings
%T Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti
%A Sakib, Fardin Ahsan
%A Karim, A. H. M. Rezaul
%A Khan, Saadat Hasan
%A Rahman, Md Mushfiqur
%Y Alam, Firoj
%Y Kar, Sudipta
%Y Chowdhury, Shammur Absar
%Y Sadeque, Farig
%Y Amin, Ruhul
%S Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F sakib-etal-2023-intent
%X As voice assistants cement their place in our technologically advanced society, there remains a need to cater to the diverse linguistic landscape, including colloquial forms of low-resource languages. Our study introduces the first-ever comprehensive dataset for intent detection and slot filling in formal Bangla, colloquial Bangla, and Sylheti languages, totaling 984 samples across 10 unique intents. Our analysis reveals the robustness of large language models for tackling downstream tasks with inadequate data. The GPT-3.5 model achieves an impressive F1 score of 0.94 in intent detection and 0.51 in slot filling for colloquial Bangla.
%R 10.18653/v1/2023.banglalp-1.6
%U https://aclanthology.org/2023.banglalp-1.6/
%U https://doi.org/10.18653/v1/2023.banglalp-1.6
%P 48-55

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Markdown (Informal)

[Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti](https://aclanthology.org/2023.banglalp-1.6/) (Sakib et al., BanglaLP 2023)

Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti (Sakib et al., BanglaLP 2023)

ACL

Fardin Ahsan Sakib, A H M Rezaul Karim, Saadat Hasan Khan, and Md Mushfiqur Rahman. 2023. Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti. In Proceedings of the First Workshop on Bangla Language Processing (BLP-2023), pages 48–55, Singapore. Association for Computational Linguistics.