Hamid R. Chinaei

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Spoken language communication between human and machines has become a challenge in research and technology. In particular, enabling the health care robots with spoken language interface is of great attention. Recently due to uncertainty characterizing dialogues, there has been interest for modelling the dialogue manager of spoken dialogue systems using(More)
In this paper, we propose an algorithm for learning a reward model from an expert policy in partially observable Markov decision processes (POMDPs). The problem is formulated as inverse reinforcement learning (IRL) in the POMDP framework. The proposed algorithm then uses the expert trajectories to find an unknown reward model-based on the known POMDP model(More)
The SmartWheeler project aims at developing an intelligent wheelchair for handicapped people. In this paper, we model the dialogue manager of SmartWheeler in MDP and POMDP frameworks using its collected dialogues. First, we learn the model components of the dialogue MDP based on our previous works. Then, we extend the dialogue MDP to a dialogue POMDP, by(More)
To support the personalization of Question Answering (QA) systems, we propose a new probabilistic scoring approach based on the topics of the question and candidate answers. First, a set of topics of interest to the user is learned based on a topic modeling approach such as Latent Dirichlet Allocation. Then, the similarity of questions asked by the user to(More)
A common problem in spoken dialogue systems is finding the intention of the user. This problem deals with obtaining one or several topics for each transcribed, possibly noisy, sentence of the user. In this work, we apply the recent unsupervised learning method, Hidden Topic Markov Models (HTMM), for finding the intention of the user in dialogues. This(More)
In business analytics, measure values, such as sales numbers or volumes of cargo transported, are often summed along values of one or more corresponding categories, such as time or shipping container. However, not every measure should be added by default (e.g., one might more typically want a mean over the heights of a set of people); similarly, some(More)
We aim to build dialogue agents that optimize the dialogue strategy, specifically through learning the dialogue model components from dialogue data. In this paper, we describe our current research on automatically learning dialogue strategies in the healthcare domain. We go through our systematic approach of learning dialogue model components from data,(More)