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  • 1.
    Berglund, Aseel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, ASLAB - Application Systems Laboratory. Linköpings universitet, Tekniska högskolan.
    Johansson, Pontus
    Linköpings universitet, Institutionen för datavetenskap. Linköpings universitet, Tekniska högskolan.
    Using speech and dialogue for interactive TV navigation2004Inngår i: Interactive Access in the Information Society (UAIS), ISSN 1615-5289, Vol. 3, nr 3-4, s. 224-238Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Interaction techniques for interactive television (iTV) are currently complex and difficult to use for a wide-range of viewers. Few previous studies have dealt with the potential benefits of multimodal dialogue interaction in the context of iTV for the purpose of flexibility, usability, efficiency, and accessibility. This paper investigates the benefits of introducing speech and connected dialogue for iTV interaction, and presents a case study in which a prototype system was built allowing users to navigate the information space and control the operation of the TV by a speech-based natural language interface. The system was evaluated by analysing the user experience in five categories capturing essential aspects of iTV interaction: interaction style, information load, data access, effectiveness and initiative. Design considerations relevant for speech and dialogue information systems for TV interfaces also emerged from the analysis.

  • 2.
    Degerstedt, Lars
    et al.
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Johansson, Pontus
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Evolutionary Development of Phase-Based Dialogue Systems2003Inngår i: Proceedings of the 8th Scandianvian Conference on Artificial Intelligence. Bergen, Norway, November 2-4, 2003., 2003, s. 59-67Konferansepaper (Fagfellevurdert)
  • 3.
    Ibrahim, Aseel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, ASLAB - Application Systems Laboratory. Linköpings universitet, Tekniska högskolan.
    Johansson, Pontus
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Multimodal Dialogue Systems: A Case Study for Interactive TV2002Inngår i: Proceedings of the 7thERCIM Workshop on User Interfaces for All. Paris, France. 2002, 2002Konferansepaper (Fagfellevurdert)
  • 4.
    Ibrahim (Berglund), Aseel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, ASLAB - Application Systems Laboratory. Linköpings universitet, Tekniska högskolan.
    Johansson, Pontus
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Multimodal Dialogue Systems for Interactive TV Applications2002Inngår i: Proceedings of the 4th IEEE International Conference on Multimodal Interfaces 2002 (ICMI’02), Pittsburgh, USA, 2002, s. 117-122Konferansepaper (Fagfellevurdert)
  • 5.
    Johansson, Pontus
    Linköpings universitet, Institutionen för datavetenskap. Linköpings universitet, Tekniska högskolan.
    Design and Development of Recommender Dialogue Systems2004Licentiatavhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    The work in this thesis addresses design and development of multimodal dialogue recommender systems for the home context-of-use. In the design part, two investigations on multimodal recommendation dialogue interaction in the home context are reported on. The first study gives implications for the design of dialogue system interaction including personalization and a three-entity multimodal interaction model accommodating dialogue feedback in order to make the interaction more efficient and successful. In the second study a dialogue corpus of movie recommendation dialogues is collected and analyzed, providing a characterization of such dialogues. We identify three initiative types that need to be addressed in a recommender dialogue system implementation: system-driven preference requests, userdriven information requests, and preference volunteering. Through the process of dialogue distilling, a dialogue control strategy covering system-driven preference requests from the corpus is arrived at.

    In the development part, an application-driven development process is adopted where reusable generic components evolve through the iterative and incremental refinement of dialogue systems. The Phase Graph Processor (PGP) design pattern is one such evolved component suggesting a phase-based control of dialogue systems. PGP is a generic and flexible micro architecture accommodating frequent change of requirements inherent of agile, evolutionary system development. As PGP has been used in a series of previous information-providing dialogue system projects, a standard phase graph has been established that covers the second initiative type; user-driven information requests. The phase graph is incrementally refined in order to provide user preference modeling, thus addressing the third initiative type, and multimodality as indicated by the user studies. In the iterative development of the multimodal recommender dialogue system MADFILM the phase graph is coupled with the dialogue control strategy in order to cater for the seamless integration of the three initiative types.

  • 6.
    Johansson, Pontus
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    MadFilm - a Multimodal Approach to Handle Search and Organization in a Movie Recommendaton System2003Inngår i: Proceedings of the 1st Nordic Symposium on Multimodal Communication. Helsingör, Denmark, September 25-26, 2003, 2003, s. 53-65Konferansepaper (Fagfellevurdert)
  • 7.
    Johansson, Pontus
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Natural Language Interaction in Personalized EPGs2003Inngår i: Proceedings of the 3rd Workshop on Personalization in TV (9th International Conference on User Modeling). Johnstown (PA), USA, June 23, 2003, 2003, s. 27-31Konferansepaper (Fagfellevurdert)
  • 8.
    Johansson, Pontus
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    User Modeling in Dialogue Systems2002Rapport (Annet vitenskapelig)
  • 9.
    Johansson, Pontus
    et al.
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Degerstedt, Lars
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Jönsson, Arne
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Iterative Developmentof an Information-Providing Dialogue System2002Inngår i: Proceedings of the 7th ERCIM Workshop on User Interfaces for All. Paris, France. 2002., 2002, s. 29-36Konferansepaper (Fagfellevurdert)
  • 10.
    Wärnestål, Pontus
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Dialogue Behavior Management in Conversational Recommender Systems2007Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    This thesis examines recommendation dialogue, in the context of dialogue strategy design for conversational recommender systems. The purpose of a recommender system is to produce personalized recommendations of potentially useful items from a large space of possible options. In a conversational recommender system, this task is approached by utilizing natural language recommendation dialogue for detecting user preferences, as well as for providing recommendations. The fundamental idea of a conversational recommender system is that it relies on dialogue sessions to detect, continuously update, and utilize the user's preferences in order to predict potential interest in domain items modeled in a system. Designing the dialogue strategy management is thus one of the most important tasks for such systems.

    Based on empirical studies as well as design and implementation of conversational recommender systems, a behavior-based dialogue model called bcorn is presented. bcorn is based on three constructs, which are presented in the thesis. It utilizes a user preference modeling framework (preflets) that supports and utilizes natural language dialogue, and allows for descriptive, comparative, and superlative preference statements, in various situations. Another component of bcorn is its message-passing formalism, pcql, which is a notation used when describing preferential and factual statements and requests. bcorn is designed to be a generic recommendation dialogue strategy with conventional, information-providing, and recommendation capabilities, that each describes a natural chunk of a recommender agent's dialogue strategy, modeled in dialogue behavior diagrams that are run in parallel to give rise to coherent, flexible, and effective dialogue in conversational recommender systems.

    Three empirical studies have been carried out in order to explore the problem space of recommendation dialogue, and to verify the solutions put forward in this work. Study I is a corpus study in the domain of movie recommendations. The result of the study is a characterization of recommendation dialogue, and forms a base for a first prototype implementation of a human-computer recommendation dialogue control strategy. Study II is an end-user evaluation of the acorn system that implements the dialogue control strategy and results in a verification of the effectiveness and usability of the dialogue strategy. There are also implications that influence the refinement of the model that are used in the bcorn dialogue strategy model. Study III is an overhearer evaluation of a functional conversational recommender system called CoreSong, which implements the bcorn model. The result of the study is indicative of the soundness of the behavior-based approach to conversational recommender system design, as well as the informativeness, naturalness, and coherence of the individual bcorn dialogue behaviors.

  • 11.
    Wärnestål, Pontus
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Modeling a Dialogue Strategy for Personalized Movie Recommendations2005Inngår i: Beyond Personalization workshop Intelligent User Interfaces 2005,2005, 2005, s. 77-82Konferansepaper (Fagfellevurdert)
  • 12.
    Wärnestål, Pontus
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Modularized User Modeling in Conversational Recommender Systems2005Inngår i: International Conference on User Modeling,2005, Berlin: Springer Verlag , 2005, s. 545-Konferansepaper (Fagfellevurdert)
  • 13.
    Wärnestål, Pontus
    Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk. Linköpings universitet, Tekniska högskolan.
    Modularized user modeling in conversational recommender systems2005Inngår i: User Modeling 2005: 10th International Conference, UM 2005, Edinburgh, Scotland, UK, July 24-29, 2005. Proceedings / [ed] Liliana Ardissono, Paul Brna and Antonija Mitrovic, Springer Berlin/Heidelberg, 2005, Vol. 3538, s. 527-529Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    My research interest lies in investigating user-adaptive interaction in a conversational setting for recommender systems, with particular focus on modularized user model components and the use of a dialogue partner (DP) in such systems.

  • 14.
    Wärnestål, Pontus
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    User Evaluation of a Conversational Recommender System2005Inngår i: Knowledge and Reasoning in Practical Dialogue Systems IJCAI 2005,2005, 2005, s. 32-39Konferansepaper (Fagfellevurdert)
  • 15.
    Wärnestål, Pontus
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Degerstedt, Lars
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Jönsson, Arne
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Emergent Conversational Recommendations: A Dialogue Behavior Approach2007Inngår i: Proceedings of the 8th SIGDIAL Workshop on Discourse and Dialogue,2007, 2007, s. 63-66Konferansepaper (Fagfellevurdert)
  • 16.
    Wärnestål, Pontus
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Degerstedt, Lars
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Jönsson, Arne
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Interview and Delivery: Dialogue Strategies for Conversational Recommender Systems2007Inngår i: Proceedings of 16th Nordic Conference of Computational Linguistics Nodalida,2007, 2007, s. 199-205Konferansepaper (Fagfellevurdert)
  • 17.
    Wärnestål, Pontus
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Degerstedt, Lars
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    Jönsson, Arne
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, NLPLAB - Laboratoriet för databehandling av naturligt språk.
    PCQL: A Formalism for Human-Like Preference Dialogues2007Inngår i: IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems,2007, 2007, s. 46-54Konferansepaper (Fagfellevurdert)
1 - 17 of 17
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