@inproceedings{2eb7fa7aa7a0445fa0298c08889237cb,
title = "SwiftSLU: An Framework for Cost-Efficient Dataset Construction and Boundary-Modifier-Aware Joint Model in Domain-Specific SLU",
abstract = "SLU datasets are highly domain-specific and require a token-level fine-grained annotation, which lead to extremely high cost for manual BIO labeling. In this paper, We introduce a cost-efficient dataset construction approach, demonstrated through the development of VehiCom, a vehicle commands SLU dataset in Chinese built from scratch. We also propose JointVehiCom, a boundary-aware and modifier-aware joint SLU model that excels in accurately identifying entity boundaries in utterances and recognizing entities within auxiliary components, achieving state-of-the-art performance.",
keywords = "Intent Detection, Slot Filling, Spoken Language Understanding, Vehicle Command",
author = "Dongdong Yang and Chong Feng and Xinyan Li",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 10th International Conference on Computer and Communication Systems, ICCCS 2025 ; Conference date: 18-04-2025 Through 21-04-2025",
year = "2025",
doi = "10.1109/ICCCS65393.2025.11069633",
language = "English",
series = "10th International Conference on Computer and Communication Systems, ICCCS 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "655--661",
booktitle = "10th International Conference on Computer and Communication Systems, ICCCS 2025",
address = "United States",
}