1 / 27

Ontology-driven VoiceXML Dialogues Generation

Ontology-driven VoiceXML Dialogues Generation. Marta Gatius, Meritxell González TALP Research Center, Technical University of Catalonia, Barcelona Berlin, 2004. Outline. Introduction Using an ontology in the dialogue design The system’s messages and grammars Describing an example

zlata
Download Presentation

Ontology-driven VoiceXML Dialogues Generation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Ontology-driven VoiceXML Dialogues Generation Marta Gatius, Meritxell González TALP Research Center, Technical University of Catalonia, Barcelona Berlin, 2004

  2. Outline • Introduction • Using an ontology in the dialogue design • The system’s messages and grammars • Describing an example • Conclusions

  3. VoiceXML strengths • Rapid and easy deployment of spoken dialogue systems • Isolation of low level details • Easy access to internet-data • The same Client/Server architecture used by many web applications

  4. VoiceXML strengths • Reusability • Across services • Subdialogues can be reused • Subdialogues for asking Names, Addresses, Telephones • Across languages • When adapting the dialogue system to another language most part of the dialogues can be reused

  5. VoiceXML strengths • Multilinguality • Accepting more than one language in a dialogue • Mixing Catalan and Spanish • Giving an address: Plaza “Francesc Macià”

  6. The dialogue design • The information the application needs from the user • The information the user needs from the application • How the information is delivered • The sequences of dialogues • The system help • Error recovering policies

  7. The different types of knowledge involved in the communication • Conceptual knowledge: • Application knowledge appearing in communication • Dialogue knowledge: • Dialogue rules controlling interaction • Linguistic knowledge: • Linguistic structures expressing the communication tasks Conceptual Ontology

  8. Using an ontology • Representing all application concepts appearing during communication • Concepts are described by a set of attributes • Dialogues consist of asking/giving the user values of the conceptual attributes Task-oriented system-driven dialogues

  9. Conceptual Ontology TRANSACTION servicetype Information Action Cancellation attribute_value(transaction, servicetype, cancellation) attribute_value(transaction, servicetype, information) attribute_value(transaction, servicetype, action)

  10. Conceptual Ontology Object_Collection Application servicetype Information Collection Object: Address: Telephone: Cancellation

  11. Using an ontology For clarification dialogues - Detecting hyperonyns and hypononyms System: “What type of object you want to throw out?” User: “An appliance” System: “What type of appliance” User: “A refrigerator”

  12. The system’s messages and grammars • They are generated from the conceptual attributes in the ontology • The attributes describing concepts are classifyied according to a semantic-syntactico taxonomy of attributes • It has been used for generating Natural Languages Interfaces from ontologies

  13. The semantic- syntactico taxonomy of attributes Generalization of the relations between • Application knowledge in the Conceptual Ontology and linguistic distinctions • Each class is related to the linguistic structures expressing the consulting and filling of the attributes in the class

  14. The basic attribute taxonomy who_does who_object • participants : • being: • possession: • descriptions and relationships between two or more objects : • related processes: what_object is has of does

  15. Conceptual Ontology Object_Collecting Application servicetype Information Collection Noun: “collection” Verb: “fixes a data for collection” Cancellation

  16. ATTRIBUTE_CLASSES OF OF_TYPE SERVICE_TYPE Asking1: “This service gives information, <action_verb> and cancels a previous request. What do you want?” Asking2: “Say what you want: information, <action_noun> or cancellation”

  17. Conceptual Ontology Object_Collecting Application servicetype Collection Noun: “collection” Verb: “fixes a data for collection” Information Cancellation Asking1: “This service gives information, fixes a data for collection and cancels a previous request. What do you want?” Asking2: “Say what you want: information, collection or cancellation”

  18. Obtaining the grammar from the Ontology public <gramservicetype> = ( <GramInf1>{:ret} | <GramC1>{:ret} | <GramA1>{:ret} ) {<@gramservicetype $ret>}; <GramInf1> = ( information ) {return("Information")}; <GramC1> = ( cancel | cancellation) {return("Cancellation")}; <GramA1> = ( [to fix a date for] collection ) {return(”Collection")};

  19. VoiceXML Document <form id="formATTRNAME"> <field name="attrATTRNAME"> <grammar src="file://grammars/gramATTRNAME.sjv" type="application/x-jsgf-flx"/> <prompt count = 1> Questionattributetype pattern1 </prompt> <prompt count = 2> Questionattributetype pattern2 </prompt> </field> </form>

  20. VoiceXML Document <form id="formservicetype"> <field name="attrservicetype"> <grammar src="file://grammars/gramservicetype.sjv" type="application/x-jsgf-flx"/> <prompt count = 1> “This service gives information, fixes a data for collection and cancels a previous request. What do you want?” </prompt> <prompt count = 2> “Say what you want: information, collection or cancellation” </prompt> </field> </form>

  21. HOPS is a three-year project focused on the deployment of advanced ICT enabled “voice-enabled front-end public platforms” in Europe permitting access for European citizens to their nearest Public Administration. HOPSEnabling an Intelligent Natural Language Based Hub for the Deployment of Advanced Semantically Enriched Multi-channel Mass-scale Online Public Services

  22. Technologies • Voice XML Portals • Natural Language Processing • Semantic Web Technologies

  23. Large Objects Collection Service • Studying the information needed for the application • Studying the information appearing in conversation • The experience of the human operator using the service • Studying the examples collected from the real dialogues

  24. Large Objects Collection Service Problematic issues in dialogue Related to the domain knowledge: the classification of the object type as • green point object: pollutant or recyclable • i.e. Fridges, ruins • not green point object: furniture, electrical appliances • i.e. TV, washing machines Inconsistencies in the samples

  25. Large Objects Collection Service Problematic issues in dialogue • Personal data • Names. It is a difficult task and not completly necessary. • Address. Its difficult. • Related to the language proficiency: • How to ask the application information in a friendly way in English

  26. Conclusions • Main contribution: • Proposing an organization of the knowledge involved in communication that improves • The development process of the VoiceXML dialogue systems • The functionality of the resulting dialogue systems

  27. Conclusions Proposing a reusable organization • The Conceptual Ontology • It provides a general framework for representing application concepts • The syntactic-semantic taxonomy of attributes • Capturing the relations between application concepts and their linguistic realization

More Related