Isard, Amy

Matheson, Colin

Many traditional dialogue systems use simple predicates to send information between a Dialogue Manager and a Natural Language Generation system. We propose a flexible RST-style interface to allow for more complex structures and multimodal output, and we place the first stage of content planning under the control of the dialogue management system with access to asystem-wide information state

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     Edinburgh Research Explorer                                      Rhetorical Structure for Natural Language Generation inDialogueCitation for published version:Isard, A & Matheson, C 2012, Rhetorical Structure for Natural Language Generation in Dialogue. inProceedings of the 16th Workshop on the Semantics and Pragmatics of Dialogue (Seinedial). pp. 1-2.Link:Link to publication record in Edinburgh Research ExplorerDocument Version:Peer reviewed versionPublished In:Proceedings of the 16th Workshop on the Semantics and Pragmatics of Dialogue (Seinedial)General rightsCopyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s)and / or other copyright owners and it is a condition of accessing these publications that users recognise andabide by the legal requirements associated with these rights.Take down policyThe University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorercontent complies with UK legislation. If you believe that the public display of this file breaches copyright pleasecontact openaccess@ed.ac.uk providing details, and we will remove access to the work immediately andinvestigate your claim.Download date: 05. Apr. 2019Rhetorical Structure for Natural Language Generation in DialogueAmy Isard and Colin MathesonInstitute for Language, Cognition and ComputationSchool of Informatics, University of Edinburgh, United Kingdom{amy.isard,colin.matheson}@ed.ac.ukAbstractMany traditional dialogue systems use sim-ple predicates to send information betweena Dialogue Manager and a Natural Lan-guage Generation system. We propose aflexible RST-style interface to allow formore complex structures and multimodaloutput, and we place the first stage of con-tent planning under the control of the dia-logue management system with access to asystem-wide information state.1 IntroductionIn many dialogue systems, a Dialogue Manager(DM) sits at the centre of the interaction, takinguser inputs and sending an output specification toa Natural Language Generation (NLG) system. Inmultimodal systems, there may be a Dialogue andInteraction Manager, and the outputs may go viaan intermediate stage where the different modali-ties are synchronised, and in other cases a plannermay take over the duties of dialogue management,but there is usually a need to store the history andto specify the language output. Where the systemhas a physical component, facial and hand ges-tures may also be specified.We propose a flexible interface between theDM and the output modalities which can be usedin a variety of human-machine dialogue domains.It is based on RST structures (Mann and Thomp-son, 1988), and is related to work by (Stent et al.,2004) who used a similar approach in MATCH,their text-based restaurant recommendation sys-tem. However in MATCH, the DM sends high-level goals to the text planner, whereas in our sys-tems, the DM performs part of the content selec-tion task (in some cases by communicating witha domain planner and/or knowledge representa-tion module), and sends a structured representa-tion to the NLG system. The potential content toexpress can come from a wide range of sources,including the dialogue history, the domain knowl-edge or the task plan. For example, the task planmay describe sequences of actions which need tobe carried out in constructing objects (Foster andMatheson, 2008).This work can be seen in the broader context ofattempting to integrate language processing, dia-logue management, and NLG more closely.2 Use CasesTo date, we have used our RST representation inthree working systems in varied domains:• the JAST system (Foster and Matheson,2008; Foster et al., 2009), which allows a hu-man to collaborate with a robot in buildingsimple wooden toys• the JAMES system (Petrick and Foster,2012; Petrick et al., 2012), a robot bartender• the Beetle II system (Dzikovska et al., 2011),a tutorial dialogue system for basic electric-ity and electronicsThe top level rhetorical structures which we useare the following:enablement where one situation or action is nec-essary (but not always sufficient) for anothersituation to action to occur. e.g. “to builda tower, insert the green bolt through the redcube and screw it into the blue cube” (JAST).elaboration where one piece of content adds fur-ther information about an object which hasalready been mentioned e.g. “the battery incircuit 5 is in a closed path which does notcontain a bulb” (Beetle II).enablementbuildjoininsert screwtower green boltredcubegreen bolt   bluecubeFigure 1: Graph representation of enablement and joinrelations<output><objects><obj id="o1" type="bolt" color="green"/><obj id="o2" type="cube" color="red"/><obj id="o3" type="cube" color="blue"/><obj id="o4" type="tower"/></objects><rst><relation type="enablement"><pred action="build" result="o4"/><relation type="join"><pred action="insert"><obj idref="o1"/><obj idref="o2"/></pred><pred action="screw"><obj idref="o1"/><obj idref="o3"/></pred></relation></pred></relation</rst><actions><action type="handover"><obj idref="o1"/></action></actions></output>Figure 2: Multimodal RST XML for enablement rela-tiondefinition where one piece of information de-fines another e.g. “it means that the batteryis damaged” (Beetle II).join which signifies a simple aggregation of twopieces of content e.g. “hello, what would youlike to drink” (JAMES).A graph of an enablement relation from JAST isshown in figure 1, and a possible surface realisa-tion for this is “to build a tower, insert the greenbolt through the red cube and screw it into the bluecube”. The multimodal XML representation ofthe RST is shown in figure 2; as well as giving thecontent to be spoken, this specifies that the robotshould hand over object o1 (the green bolt) to theuser.3 ConclusionsWe designed a flexible interface for communica-tions between the Dialogue Manager and the Nat-ural Language Generation components in a di-alogue system. We have used the interface ina number of different systems, and shown thatit encourages the integration of multimodal out-put modalities. The systems we have describedall use rule-based Dialogue Management or Plan-ning, but the RST could also be used in a statis-tical dialogue system as long as the NLG compo-nent is grammar-based.ReferencesMyroslava O. Dzikovska, Amy Isard, Peter Bell, Jo-hanna D. Moore, Natalie Steinhauser, and Gwen-dolyn Campbell. 2011. Beetle ii: an adaptable tuto-rial dialogue system. In Proceedings of the 12th An-nual SIGdial Meeting on Discourse and Dialogue,demo session.Mary Ellen Foster and Colin Matheson. 2008. Fol-lowing assembly plans in cooperative, task-basedhuman-robot dialogue. In Proceedings of the 12thWorkshop on the Semantics and Pragmatics of Dia-logue (Londial 2008), London, June.Mary Ellen Foster, Manuel Giuliani, Amy Isard, ColinMatheson, Jon Oberlander, and Alois Knoll. 2009.Evaluating Description and Reference Strategies ina Cooperative Human-Robot Dialogue System. InProceedings of the Twenty-first International JointConference on Artificial Intelligence (IJCAI-09),Pasadena, California, July.William C. Mann and Sandra A. Thompson. 1988.Rhetorical Structure Theory: Toward a functionaltheory of text organization. Text, 8(3):243–281.Ronald P. A. Petrick and Mary Ellen Foster. 2012.What would you like to drink? recognising andplanning with social states in a robot bartenderdomain. In International Workshop on CognitiveRobotics (CogRob 2012) at AAAI 2012, Toronto,ON, Canada, July.Ronald P. A. Petrick, Mary Ellen Foster, and AmyIsard. 2012. Social state recognition andknowledge-level planning for human-robot interac-tion in a bartender domain. In AAAI 2012 Work-shop on Grounding Language for Physical Systems,Toronto, ON, Canada, July.Amanda Stent, R. Prasad, and M. Walker. 2004.Trainable sentence planning for complex informa-tion presentations in spoken dialog systems. In Pro-ceedings of ACL.

Rhetorical Structure for Natural Language Generation in Dialogue

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Rhetorical Structure for Natural Language Generation in Dialogue

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