Spoken dialogue system has an uncertain parameter during the speech recognition which controls its performance that vary for the different users as well as for the same user during multiple repetitions of even the same dialogue. This paper discusses how recognition errors in the users utterances can be handled by making use of semi-supervised learning techniques over the hidden vector state (HV...

Recent advancements in the area of spoken language processing and the wide acceptance of portable devices, have attracted significant interest in spoken dialogue systems. These conversational systems are man-machine interfaces which use natural language (speech) as the medium of interaction. In order to conduct dialogues, computers must have the ability to decide when and what information has t...

Dialogue model design for spoken language dialogue systems (SLDSs) is still based mainly on common sense, experience and intuition, and trial and error, rather than on established design principles. Co-operativity in dialogue is crucial to habitable human-machine spoken dialogue. The paper presents a set of principles of co-operative user-system dialogue which have been derived from a corpus of...

Dialogue act labels are being used to represent a higher level intention of utterances during human conversation (Stolcke et al., 2000). Automatic dialogue act recognition is still an active research topic. The conventional approach is to train one generic classifier using a large corpus of annotated utterances (Stolcke et al., 2000). One aspect that makes it so challenging is that people can e...

Spoken dialogue systems promise eecient and natural access to a large variety of information sources and services from any phone. However, current spoken dialogue systems are deecient in their strategies for preventing, identifying and repairing problems that arise in the conversation. This paper reports results on automatically training a Problematic Dialogue Predictor to predict problematic h...

It has been very difficult to develop spoken dialogue systems with high domain extensibility. Not only the system complexity inevitably increases with the number of topics and domains, but the concurrent topics need to be handled persistently and consistently across different domains. This paper presents a distributed architecture for cooperative spoken dialogue agents with high domain extensib...

Spoken dialogue systems promise eecient and natural access to a large variety of information sources and services from any phone. However, current spoken dialogue systems are deecient in their strategies for preventing, identifying and repairing problems that arise in the conversation. This paper reports results on automatically training a Problematic Dialogue Predictor to predict problematic h...

ITSPOKE is a spoken dialogue system that uses the Why2-Atlas text-based tutoring system as its “back-end”. A student first types a natural language answer to a qualitative physics problem. ITSPOKE then engages the student in a spoken dialogue to provide feedback and correct misconceptions, and to elicit more complete explanations. We are using ITSPOKE to generate an empirically-based understand...

For a multi-domain spoken dialogue system, there are two major difficulties in building its dialogue management. One is to interpret users' interested domain correctly and switch between domains smoothly. The other is the high cost of merging the dialogue management of different application domains. To solve these problems, an implicit domain identification and switching mechanism for dialogue ...