Paper Info
Title
Estimation of User's Internal State before the User's First Utterance Using Acoustic Features and Face Orientation
Abstract
Introduction of user models (e.g. models of a user's belief, skill and familiarity to the system) is believed to increase flexibility of response of a dialogue system. Conventionally, the internal state is estimated based on linguistic information of the previous utterance, but this approach cannot applied to the user who did not make an input utterance in the first place. Thus, we are developing a method to estimate an internal state of a spoken dialogue system's user before his/her input utterance. In a previous report, we used three acoustic features and a visual feature based on manual labels. In this paper, we introduced new features for the estimation: length of filled pause and face orientation angles. Then, we examined effectiveness of the proposed features by experiments. As a result, we obtained a three-class discrimination accuracy of 85.6% in an open test, which was 1.5 point higher than the result obtained using the previous feature set.
Year
DOI
Venue
2012
10.1109/HSI.2012.13
HSI
Keywords
Field
DocType
face recognition,feature extraction,speech processing,user interfaces,acoustic feature,dialogue system,face orientation,face orientation angle feature,filled pause length feature,linguistic information,spoken dialogue system,three-class discrimination accuracy,user belief,user familiarity,user input utterance,user internal state estimation,user model,user skill,multimodal information,non-verbal information,spoken dialogue system,user modeling
Rule-based machine translation,Speech processing,Facial recognition system,Computer science,Utterance,Speech recognition,Feature extraction,Natural language processing,User modeling,Artificial intelligence,Feature based,User interface
Conference
ISSN
Citations 
PageRank 
2158-2246
1
0.40
References 
Authors
8
3
Name
Order
Citations
PageRank
Yuya Chiba186.96
Masashi Ito2175.86
Akinori Ito327262.32