A persian benchmark for joint intent detection and slot filling | ||
| AUT Journal of Mathematics and Computing | ||
| مقاله 4، دوره 7، شماره 4، زمستان 2026، صفحه 407-422 اصل مقاله (2.55 M) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajmc.2025.23058.1225 | ||
| نویسندگان | ||
| Masoud Akbari1؛ Amirhosein Karimi1؛ Tayyebeh Saeedi1؛ Zeinab Saeidi1؛ Kiana Ghezelbash1؛ Fatemeh Shamsezat2؛ Mohammad Akbari1؛ Ali Mohades Khorasani* 1 | ||
| 1Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran | ||
| 2Department of Computer Science, Faculty of Mathematics and Computer, Fasa University, Fasa, Iran | ||
| چکیده | ||
| Natural Language Understanding ($\textbf{NLU}$) is important in today's technology as it enables machines to comprehend and process human languages, leading to improved human-computer interactions and advancements in fields such as virtual assistants, chatbots, and language-based AI systems. This paper highlights the significance of advancing the field of $\textbf{NLU}$ for low-resource languages. With intent detection and slot filling being crucial tasks in $\textbf{NLU}$, the widely used datasets $\textbf{ATIS}$ and $\textbf{SNIPS}$ have been utilized in the past. However, these datasets only cater to the English language and do not support other languages. In this work, we aim to address this gap by creating a Persian benchmark for joint intent detection and slot filling based on the $\textbf{ATIS}$ dataset. To evaluate the effectiveness of our benchmark, we employ state-of-the-art methods for intent detection and slot filling. | ||
| کلیدواژهها | ||
| ATIS dataset؛ Persian benchmark؛ Intent detection؛ Slot filling | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 756 تعداد دریافت فایل اصل مقاله: 53 |
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