Good grief, i can speak it! Preliminary experiments in audio restaurant reviews

In this paper, we introduce a new envisioned application for speech which allows users to enter restaurant reviews orally via their mobile device, and, at a later time, update a shared and growing database of consumer-provided information about restaurants. During the intervening period, a speech recognition and NLP based system has analyzed their audio recording both to extract key descriptive phrases and to compute sentiment ratings based on the evidence provided in the audio clip. We report here on our preliminary work moving towards this goal. Our experiments demonstrate that multi-aspect sentiment ranking works surprisingly well on speech output, even in the presence of recognition errors. We also present initial experiments on integrated sentence boundary detection and key phrase extraction from recognition output

Enabling browsing in interactive systems

In this thesis, we examine algorithms for content selection and information presentation that enable browsing as an information-seeking strategy. Our hypothesis is that users who wish to explore the contents of a particular domain might not be satisfied with traditional spoken dialogue systems, in which focal information is not described until a small number of the records comprising the domain are identified through a constraint-elicitation process. Specifically, we hypothesized that users would prefer responses in the form of incremental summaries of the focal information.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Learning database content for spoken dialogue system design

Spoken dialogue systems are common interfaces to backend data in information retrieval domains. As more data is made available on the Web and IE technology matures, dialogue systems, whether they be speech- or text-based, will be more in demand to provide user-friendly access to this data. However, dialogue systems must become both easier to configure, as well as more informative than the traditional form-based systems that are currently available. We present techniques in this paper to address the issue of automating both content selection for use in summary responses and in system initiative queries. 1

Hypothesis selection and resolution in the MERCURY flight reservation system

seneff,joe¡£¢¥¤§¦¨¤� © ¦¨��¤� © ������ © ��������

An analysis of automatic content selection algorithms for spoken dialogue system summaries

Previous work on information presentation in dialogue systems has argued that a user model is essential for selecting utterance content. Other work claims that the ability to browse the data is critical for supporting information-seeking behaviors in information retrieval applications, but does not specify how to provide browsing support. In this work, we test the hypothesis that automatically constructed summaries based on the current dialogue state and provided incrementally during the dialogue can support users ’ browsing activities. We examine the impact of three factors on summary efficacy: (1) the number and type of attributes selected for summary construction; (2) the use of a decision theoretic user model; and (3) the use of association rules derived automatically from the database subset currently in-focus. Our experimental results show that equally effective summaries can be constructed using either a combination of a user model with association rules, or the “Refiner ” method described in previous work. Index Terms — natural language interfaces, user modeling 1