Identifying User Intents in Vietnamese Spoken Language Commands and Its Application in Smart Mobile Voice Interaction

Abstract

This paper presents a lightweight machine learning model and a fast conjunction matching method to the problem of identifying user intents behind their spoken text commands. These model and method were integrated into a mobile virtual assistant for Vietnamese (VAV) to understand what mobile users mean to carry out on their smartphones via their commands. User intent, in the scope of our work, is an action associated with a particular mobile application. Given an input spoken command, its application will be identified by an accurate classifier while the action will be determined by a flexible conjunction matching algorithm.

DOI: 10.1007/978-3-662-49381-6_19

Cite this paper

@inproceedings{Ngo2016IdentifyingUI, title={Identifying User Intents in Vietnamese Spoken Language Commands and Its Application in Smart Mobile Voice Interaction}, author={Thi-Lan Ngo and Van-Hop Nguyen and Thi-Hai-Yen Vuong and Thac-Thong Nguyen and Thi-Thua Nguyen and Bao-Son Pham and Xuan-Hieu Phan}, booktitle={ACIIDS}, year={2016} }