eprintid: 1529
rev_number: 9
eprint_status: archive
userid: 243
dir: disk0/00/00/15/29
datestamp: 2016-05-23 05:24:00
lastmod: 2016-05-23 05:24:43
status_changed: 2016-05-23 05:24:00
type: conference_item
metadata_visibility: show
creators_name: Ngo, Thi Lan
creators_name: Pham, Bao Son
creators_name: Phan, Xuan Hieu
creators_id: sonpb@vnu.edu.vn
creators_id: hieupx@vnu.edu.vn
title: Identifying User Intents in Vietnamese Spoken Language Commands and Its Application in Smart Mobile Voice Interaction
ispublished: pub
subjects: IT
divisions: fac_fit
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. 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.
date: 2016-03-26
date_type: published
full_text_status: public
pres_type: poster
event_title: SW4PHD: the 2016 Scientific Workshop for PhD Students
event_location: Hanoi
event_dates: 26 March 2016
event_type: workshop
refereed: FALSE
citation:   Ngo, Thi Lan and Pham, Bao Son and Phan, Xuan Hieu  (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.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1529/1/42x36_phdposters_NgoThiLan.pdf