TamilATIS: Dataset for Task-Oriented Dialog in Tamil

被引：0

作者：

Ramaneswaran, S. ^{[1
]}

Vijay, Sanchit ^{[1
]}

Srinivasan, Kathiravan ^{[1
]}

机构：

[1] Vellore Inst Technol, Vellore, Tamil Nadu, India

来源：

PROCEEDINGS OF THE SECOND WORKSHOP ON SPEECH AND LANGUAGE TECHNOLOGIES FOR DRAVIDIAN LANGUAGES (DRAVIDIANLANGTECH 2022) | 2022年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Task-Oriented Dialogue (TOD) systems allow users to accomplish tasks by giving directions to the system using natural language utterances. With the widespread adoption of conversational agents and chat platforms, TOD has become mainstream in NLP research today. However, developing TOD systems require massive amounts of data, and there has been limited work done for TOD in low-resource languages like Tamil. Towards this objective, we introduce TamilATIS - a TOD dataset for Tamil which contains 4874 utterances. We present a detailed account of the entire data collection and data annotation process. We train state-of-the-art NLU models and report their performances. The Joint BERT model with XLMRoberta as utterance encoder achieved the highest score with an intent accuracy of 96.26% and slot F1 of 94.01%.

引用

页码：25 / 32

页数：8

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