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  • 1.
    Boye, Johan
    et al.
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Fredriksson, M.
    Götze, Jana
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Gustafson, Joakim
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Königsmann, J.
    Walk this way: Spatial grounding for city exploration2012In: IWSDS, 2012Conference paper (Refereed)
  • 2.
    Boye, Johan
    et al.
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Fredriksson, Morgan
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Götze, Jana
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Gustafson, Joakim
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Königsmann, Jurgen
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Walk this way: Spatial grounding for city exploration2014In: Natural interaction with robots, knowbots and smartphones, Springer-Verlag , 2014, p. 59-67Chapter in book (Refereed)
    Abstract [en]

    Recently there has been an interest in spatially aware systems for pedestrian routing and city exploration, due to the proliferation of smartphones with GPS receivers among the general public. Since GPS readings are noisy, giving good and well-timed route instructions to pedestrians is a challenging problem. This paper describes a spoken-dialogue prototype for pedestrian navigation in Stockholm that addresses this problem by using various grounding strategies.

  • 3.
    Fredriksson, Morgan
    et al.
    Liquid Media.
    Königsmann, Jugen
    Liquid Media.
    Bartie, Phil
    Edinburgh University.
    Boye, Johan
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Dalmas, Tiphaine
    Edinburgh University.
    Götze, Jana
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Mollevik, Johan
    Umeå University.
    Janarthanam, Srini
    Heriot Watt.
    Lemon, Oliver
    Heriot Watt.
    Liu, Xingkun
    Heriot Watt.
    Minock, Michael
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    D5.2.2: Final city search SpaceBook prototype2014Report (Other academic)
  • 4.
    Götze, Jana
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Talk the walk: Empirical studies and data-driven methods for geographical natural language applications2016Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Finding the way in known and unknown city environments is a task that all pedestrians carry out regularly. Current technology allows the use of smart devices as aids that can give automatic verbal route directions on the basis of the pedestrian's current position. Many such systems only give route directions, but are unable to interact with the user to answer clarifications or understand other verbal input. Furthermore, they rely mainly on conveying the quantitative information that can be derived directly from geographic map representations: 'In 300 meters, turn into High Street'. However, humans are reasoning about space predominantly in a qualitative manner, and it is less cognitively demanding for them to understand route directions that express such qualitative information, such as 'At the church, turn left' or 'You will see a café'. This thesis addresses three challenges that an interactive wayfinding system faces in the context of natural language generation and understanding: in a given situation, it must decide on whether it is appropriate to give an instruction based on a relative direction, it must be able to select salient landmarks, and it must be able to resolve the user's references to objects. In order to address these challenges, this thesis takes a data-driven approach: data was collected in a large-scale city environment to derive decision-making models from pedestrians' behavior. As a representation for the geographical environment, all studies use the crowd-sourced Openstreetmap database. The thesis presents methodologies on how the geographical and language data can be utilized to derive models that can be incorporated into an automatic route direction system.

  • 5.
    Götze, Jana
    et al.
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Boye, Johan
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Deriving Salience Models from Human Route Directions2013In: Workshop on Computational Models of Spatial Language Interpretation and Generation 2013: (CoSLI-3), 2013Conference paper (Refereed)
    Abstract [en]

    We present an approach to derive individual preferences in the use of landmarks for route instructions in a city environment. Each possible landmark that a person can refer to in a given situation is modelled as a feature vector, and the preference (or salience) associated with the landmark can be computed as a weighted sum of these features. The weight vector, representing the person's personal salience model, is automatically derived from the person's own route descriptions. Experiments show that the derived salience models can correctly predict the user's choice of landmark in 69% of the cases.

  • 6.
    Götze, Jana
    et al.
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Boye, Johan
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Learning Landmark Salience Models from Users' Route Instructions2016In: Journal of Location Based Services, ISSN 1748-9725, Vol. 10, no 1, p. 47-63Article in journal (Refereed)
    Abstract [en]

    Route instructions for pedestrians are usually better understood if they include references to landmarks, and moreover, these landmarks should be as salient as possible. In this paper, we present an approach for automatically deriving a mathematical model of salience directly from route instructions given by humans. Each possible landmark that a person can refer to in a given situation is modelled as a feature vector, and the salience associated with each landmark can be computed as a weighted sum of these features. We use a ranking SVM method to derive the weights from route instructions given by humans as they are walking the route. The weight vector, representing the person’s personal salience model, determines which landmark(s) are most appropriate to refer to in new situations.

  • 7.
    Götze, Jana
    et al.
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Boye, Johan
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Resolving spatial references using crowdsourced geographical data2015In: Proceedings of the 20th Nordic Conference of Computational Linguistics, NODALIDA 2015, Linköping University Electronic Press, 2015, p. 61-68Conference paper (Refereed)
    Abstract [en]

    We present a study in which we seek to interpret spatial references that are part of in-situ route descriptions. Our aim is to resolve these references to actual entities and places in the city using a crowdsourced geographic database (OpenStreetMap). We discuss the problems related to this task, and present a possible automatic reference resolution method that can find the correct referent in 68% of the cases using features that are easily computable from the map.

  • 8.
    Götze, Jana
    et al.
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Boye, Johan
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    "Turn left" vs. "Walk towards the cafe": When relative directions work better than landmarks2015In: AGILE 2015: Geographic Information Science as an Enabler of Smarter Cities and Communities. Part III / [ed] Bacao, F., M.Y. Santos, M. Painho, Springer Publishing Company, 2015, p. 253-267Chapter in book (Refereed)
    Abstract [en]

    An automatic mechanism that gives verbal navigation instructions to pedestrians in situ needs to take into account a number of factors. Besides giving the instruction at the righttime and place, the information needs to be as unambiguous as possible for the user to both choose the correct path and be confident in doing so. Humans make extensive use of landmarks when describ-ing the way to others and are more successful following instructions that in-clude landmarks. We present a study comparing landmark-based instructions with relative direction instructions on pedestrians in a real city environment, measuring both objective and subjective success. We find that atsome deci-sion points, relative direction instructions work better. We present a method that uses openly available geographic data to predict which kindof instruction is preferable ata given decision point.

  • 9.
    Götze, Jana
    et al.
    KTH.
    Johan, Boye
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Reference resolution for pedestrian wayfinding systems2017In: 20th AGILE International Conference on Geographic Information Science, 2017, Kluwer Academic Publishers , 2017, p. 59-75Conference paper (Refereed)
    Abstract [en]

    References to objects in our physical environment are common especially in language about wayfinding. Advanced wayfinding systems that interact with the pedestrian bymeans of (spoken) natural language therefore need to be able to resolve references given by pedestrians (i.e. understand what entity the pedestrian is referring to). The contribution of this paper is a probabilistic approach to reference resolution in a large-scale, real city environment, where the context changes constantly as the pedestrians are moving. The geographic situation, including information about objects’ location and type, is represented using OpenStreetMap data.

  • 10. Götze, Jana
    et al.
    Scheffler, Tatjana
    Roller, Roland
    Reithinger, Norbert
    User simulation for the evaluation of bus information systems2010In: 2010 IEEE Workshop on Spoken Language Technology, SLT 2010 - Proceedings, 2010, p. 454-459Conference paper (Refereed)
    Abstract [en]

    In this paper, we describe our contribution to the Spoken Dialog Challenge. We set up a user simulation using the large Let’s Go corpus as resource to build our models. Automatic calls were made to all four dialog systems in the SDC, bus information systems that cover the schedule of Pittsburgh, PA. We discuss in detail the architecture and required setup for our system-independent user simulation and report the results and challenges we faced. We also report initial evaluation results.

  • 11. Janarthanam, S.
    et al.
    Lemon, O.
    Liu, X.
    Bartie, P.
    Mackaness, W.
    Dalmas, T.
    Götze, Jana
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Conversational Natural Language Interaction for Place-related Knowledge Acquisition2012In: Place-related Knowledge Acquisition Research Workshop (PKAR), Spatial Cognition Conference, 2012, p. 33-38Conference paper (Refereed)
    Abstract [en]

    We focus on the problems of using Natural Language interaction to support pedestrians in their place-related knowledge acquisition. Our case study for this discussion is a smartphone-based Natural Language interface that allows users to acquire spatial and cultural knowledge of a city. The framework consists of a spoken dialogue-based information system and a smartphone client. The system is novel in combining geographic information system (GIS) modules such as a visibility engine with a question-answering (QA) system. Users can use the smartphone client to engage in a variety of interleaved conversations such as navigating from A to B, using the QA functionality to learn more about points of interest (PoI) nearby, and searching for amenities and tourist attractions. This system explores a variety of research questions involving Natural Language interaction for acquisition of knowledge about space and place.

  • 12. Janarthanam, S.
    et al.
    Lemon, O.
    Liu, X.
    Bartie, P.
    Mackaness, W.
    Dalmas, T.
    Götze, Jana
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Integrating location, visibility, and Question-Answering in a spoken dialogue system for pedestrian city exploration2012In: Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), 2012, p. 134-136Conference paper (Refereed)
    Abstract [en]

    We demonstrate a spoken dialogue-based information system for pedestrians. The system is novel in combining geographic information system (GIS) modules such as a visibility engine with a question-answering (QA) system, integrated within a dialogue system architecture. Users of the demonstration system can use a web-based version (simulating pedestrian movement using StreetView) to engage in a variety of interleaved conversations such as navigating from A to B, using the QA functionality to learn more about points of interest (PoI) nearby, and searching for amenities and tourist attractions. This system explores a variety of research questions involving the integration of multiple information sources within conversational interaction.

  • 13. Janarthanam, S.
    et al.
    Lemon, O.
    Liu, X.
    Bartie, P.
    Mackaness, W.
    Dalmas, T.
    Götze, Jana
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Integrating location, visibility, and Question-Answering in a spoken dialogue system for pedestrian city exploration2012In: Proceedings of SemDial 2012 (SeineDial): The 16th Workshop on the Semantics and Pragmatics of Dialogue / [ed] Sarah Brown-Schmidt, Jonathan Ginzburg, Staffan Larsson, 2012, p. 157-158Conference paper (Refereed)
    Abstract [en]

    We demonstrate a spoken dialogue-based information system for pedestrians. The system is novel in combining geographic information system (GIS) modules such as a visibility engine with a question-answering (QA) system,integrated within a dialogue system architecture. Users of the demonstration system can use a web-based version (simulating pedestrian movement using StreetView) to engage in a variety of interleaved navigation and QA conversations.

  • 14.
    Oertel, Catharine
    et al.
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Salvi, Giampiero
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Götze, Jana
    KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
    Edlund, Jens
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Gustafson, Joakim
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Heldner, Mattias
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    The KTH Games Corpora: How to Catch a Werewolf2013In: IVA 2013 Workshop Multimodal Corpora: Beyond Audio and Video: MMC 2013, 2013Conference paper (Refereed)
  • 15. Strömbergsson, S.
    et al.
    Edlund, Jens
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Götze, Jana
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH. Karolinska Institutet (KI), Sweden.
    Björkenstam, K. N.
    Approximating phonotactic input in children's linguistic environments from orthographic transcripts2017In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, International Speech Communication Association , 2017, Vol. 2017, p. 2213-2217Conference paper (Refereed)
    Abstract [en]

    Child-directed spoken data is the ideal source of support for claims about children's linguistic environments. However, phonological transcriptions of child-directed speech are scarce, compared to sources like adult-directed speech or text data. Acquiring reliable descriptions of children's phonological environments from more readily accessible sources would mean considerable savings of time and money. The first step towards this goal is to quantify the reliability of descriptions derived from such secondary sources. We investigate how phonological distributions vary across different modalities (spoken vs. written), and across the age of the intended audience (children vs. adults). Using a previously unseen collection of Swedish adult-and child-directed spoken and written data, we combine lexicon look-up and graphemeto-phoneme conversion to approximate phonological characteristics. The analysis shows distributional differences across datasets both for single phonemes and for longer phoneme sequences. Some of these are predictably attributed to lexical and contextual characteristics of text vs. speech. The generated phonological transcriptions are remarkably reliable. The differences in phonological distributions between child-directed speech and secondary sources highlight a need for compensatory measures when relying on written data or on adult-directed spoken data, and/or for continued collection of actual child-directed speech in research on children's language environments.

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