Thi Lan Ngo and Bao Son Pham and Xuan Hieu Phan (2016) Identifying User Intents in Vietnamese Spoken Language Commands and Its Application in Smart Mobile Voice Interaction. In: SW4PHD: the 2016 Scientific Workshop for PhD Students, 26 March 2016, Hanoi.
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. Our classifier and conjunction matcher are very compact in order that we can store and execute them right on mobile devices. To evaluate the classifier and the matcher, we annotated a medium–sized data set, conducting various experiments with different settings, and achieving impressive accuracy for both the application and action identification.
|Item Type:||Conference or Workshop Item (Poster)|
|Subjects:||Information Technology (IT)|
|Divisions:||Faculty of Information Technology (FIT)|
|Deposited By:||Dr Ngoc Thang Bui|
|Deposited On:||23 May 2016 05:24|
|Last Modified:||23 May 2016 05:24|
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