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Ontology-driven VoiceXML Dialogues Generation

Ontology-driven VoiceXML Dialogues Generation

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Ontology-driven VoiceXML Dialogues Generation

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  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