NDLI: A nonparametric Bayesian approach to learning multimodal interaction management

Content Provider	IEEE Xplore Digital Library
Author	Zhuoran Wang Lemon, O.
Copyright Year	2012
Description	Author affiliation: MACS, Heriot-Watt University, Edinburgh, UK (Zhuoran Wang; Lemon, O.)
Abstract	Managing multimodal interactions between humans and computer systems requires a combination of state estimation based on multiple observation streams, and optimisation of time-dependent action selection. Previous work using partially observable Markov decision processes (POMDPs) for multimodal interaction has focused on simple turn-based systems. However, state persistence and implicit state transitions are frequent in real-world multimodal interactions. These phenomena cannot be fully modelled using turn-based systems, where the timing of system actions is a non-trivial issue. In addition, in prior work the POMDP parameterisation has been either hand-coded or learned from labelled data, which requires significant domain-specific knowledge and is labor-consuming. We therefore propose a nonparametric Bayesian method to automatically infer the (distributional) representations of POMDP states for multimodal interactive systems, without using any domain knowledge. We develop an extended version of the infinite POMDP method, to better address state persistence, implicit transition, and timing issues observed in real data. The main contribution is a “sticky” infinite POMDP model that is biased towards self-transitions. The performance of the proposed unsupervised approach is evaluated based on both artificially synthesised data and a manually transcribed and annotated human-human interaction corpus. We show statistically significant improvements (e.g. in ability of the planner to recall human bartender actions) over a supervised POMDP method.
Starting Page	1
Ending Page	6
File Size	713033
Page Count	6
File Format	PDF
ISBN	9781467351256
e-ISBN	9781467351263
e-ISBN	9781467351249
DOI	10.1109/SLT.2012.6424162
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multimodal Interaction HDP Humans Hidden Markov models POMDP Speech recognition Speech Timing Planning Standards
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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