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Evolució dels sistemes de diàleg

Evolució dels sistemes de diàleg. Millorar el procés de desenvolupament del sistema Millorar la funcionalitat Utilizació en aplicacions més complexes Expansió de la cobertura lingüística Millora del controlador de diàleg Utilització del model del diàleg

jescie-rodgers
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Evolució dels sistemes de diàleg

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  1. Evolució dels sistemes de diàleg • Millorar el procés de desenvolupament del sistema • Millorar la funcionalitat • Utilizació en aplicacions més complexes • Expansió de la cobertura lingüística • Millora del controlador de diàleg • Utilització del model del diàleg • Utilització del model de tasques del sistema • Integració amb altres modes: multimodalitat

  2. Evolució Millorar el procés de desenvolupament del sistema • Transportables a dominis diferents • Sistemes i eines per desenvolupar mòduls comunicatius • INKA: Interfícies per construir Sistemes Experts • Utilitza un Llenguate Structurat d’Interfícies • NL-MENU: Interfícies per consultar bases de dades • NAT: Interfícies per diferents llenguatges i aplicacions

  3. Evolució Utilizació en aplicacions més complexes Interfícies en LN per sistemes basats en el coneixement • El coneixement conceptual implicat és més complexe • Es necessiten noves functionalitats • Preguntes sobre l’aplicació • El coneixement lingüístic necessari és més gran Incorporació de la representació del domini

  4. Evolució Expansió de la cobertura linguística Eficiència Cobertura Reusabilitat Basats en templetes orientats a la tasca Bona Pobre Difícil • Recursos generals adaptables a diferents aplicacions Bona Rica Fàcill Recursos generals Pobre Rica Fàcil

  5. Integració amb altres modes: multimodalitat • La integració de speech permet una comunicació més amistosa i noves aplicacions • VOYAGER (MIT), Office Manager (CMU), MASK (Multimodal Multimedia Automated Service Kiosk), ATIS (MIT, CMU), Railtel, Sundial, Verbmobil • La integració amb menus, gràfics i gest millora la communicació en moltes aplicacions • MMI2 (Multimodal Interface for Man Machine Interaction) • MATIS (Multimodal Airline Travel Information System) • COMET (Coordinated Multimedia Explanation Testbed), ALFresco, CUBRICON

  6. The functionality of GISE GISE: Generador de Interfaces para Sistemas Expertos • It supports NL communication with KBSs • It automatically adapts • General linguistic knowledge • Represented in a Linguistic Ontology • To application communication tasks • Represented in aConceptual Ontology

  7. Aim of the study GISE, a systemforimproving NL Interaction with Knowledge Based Systems • Reducing the run-time requirements for processing user interventions • Guiding the user about the system capabilities • Reducing the cost of developing the grammar and lexicon • The GISE NLI uses: • - An application-restricted grammar and lexicon • - A menu-system • GISE automatically adapts • - General linguistic knowledge to the application • knowledge represented in a Conceptual Ontology

  8. GISE The different types of knowledge involved in the generation process • Conceptual knowledge: • Application knowledge appearing in communication • Communication tasks: general and specific • Linguistic knowledge: • Linguistic structures expressing the communication tasks • Control knowledge: • Controlling the process of relating general linguistic knowledge to application knowledge Conceptual Ontology Linguistic Ontology Control Rules

  9. GISE Obtaining the application-restricted linguistic resources Step 3. Adapting general linguistic knowledge to express the application communication tasks Step 1. Providing the application domain-specific knowledge Step 2. Adapting the general communication tasks to cover application knowledge

  10. The functionality of GISE Obtaining the application-restricted linguistic resources Data Description Dialogue system Conceptual Ontology General knowledge Control Description Application grammar Application lexicon Application knowledge Control rules Linguistic Ontology General knowledge Application lexicon

  11. The architecture of GISE The Conceptual Ontology • There are 3 basic entities represented in 3 separated taxonomies • Concepts • Attributes • Describing the concepts • They are classified according to a syntacico-semantic taxonomy • Operations • The communication tasks consist of the expression of allowed operations over the CO concepts

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

  13. Conceptual Ontology 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

  14. Conceptual Ontology TOP CONCEPT ATTRIBUTE OPERATION TRANSPORT lex: (transporte) departure arrival departuretime arrivaltime price TRAIN BUS

  15. Conceptual Ontology ATTRIBUTE OF OF_QUANTITY OF_TIME OF_COST ARRIVALTIME lex: (llegar,...) unit: h/m DEPARTURETIME lex: (hora_salida, salir,..) unit: h/m PRICE lex: (precio,..) unit: Euro

  16. Conceptual Ontology TOP CONCEPT ATTRIBUTE OPERATION MINIMUM_ATTRIBUTE_VALUE_O concept attribute OF_TIME OF_COST Which <concept_name> <attribute_verb> first? TRAIN lex: (tren) departure arrival departuretime arrivaltime price Which is the cheapest <concept_name> ? Which train departures first? Which train arrives first? Which is the cheapest train?

  17. Conceptual Ontology Operations • Operations are represented as CO objects • The attributes describing these objects represent their parameters and their preconditions (the conditions that must hold for an operation to be executed) • They are classified as Simple or complex • Constructive • Creating a conceptual instance, filling attributes • Consultative • Consulting the value of an instance attribute

  18. The architecture of GISE The Linguistic Knowledge • It is organized following the basic principles of the Nigel grammar • It covers the Spanish communication with KBSs • It is represented as an ontology • A large systemic functional grammar of English • It is based on Hallidays’s work • It has been used with GUM to generate NL

  19. The grammar and lexicon generated • Their size is not large -> Simple parsing • They cover only the domain communication tasks • They incorporate dynamic categories • They incorporate information from the Conceptual Ontology-> Simple semantic interpretation • In the lexical entries • In the features augmenting the categories • In the preconditions associated with the rules

  20. Linguistic Ontology • Linguistic knowledge is organized in two dimensions: • Rank: The scale of the grammatical structures represented • Clause • Group • Word • Metafunction: The type of meaning • Interpersonal: The type of interaction • Ideational: The propositional meaning and content • Textual: The information organization

  21. The architecture of GISE The control rules • They control the process of adapting the general linguistic knowledge to applications • They establish general relations between: • Concepts and operations in the CO • CO and LO objects • Their form is: conditions ----> actions • They are implemented in PRE(Production • Rules Environment)

  22. The control rules Adapting the general communication tasks to cover application knowledge for each CONCEPTin ONTOLOGY do generate_CO_operations_ instance_modifying_concept (CONCEPT) generate_CO_operations_ instance_consulting_concept (CONCEPT) endfor

  23. The control rules Adapting general linguistic knowledge to express the application communication tasks for each OPERATION_INSTANCEin ONTOLOGY do generate_CLAUSE_instances (OPERATION_INSTANCE) for eachARGUMENTinOPERATION_INSTANCEdo generate_GROUP/WORD_instances (OPERATION_INSTANCE , ARGUMENT) endfor endfor

  24. The control rules The basic set of rules • It controls the generation of grammars and lexicons for each application • It contains 48 rules organized in 8 rulesets • It covers different types of interfaces • It can be enlarged easily Interfaces supporting descriptions Interfaces supporting consults Interfaces supporting consults and descriptions

  25. The control rules A rule of the ruleset creating_instance (rule cio ruleset creating_instance priority 1 control forever (object ^con ?con ^pcc ?pcc) ---> (?crinno := (create-name ‘criwno ?con) (?concrinno := (create-object ?crinno ‘crinno)) (?oparg := (add-slots ?crinno ‘((con ?con)(pcc ?pcc)))) ...)

  26. The dialogue system User Dialogue sytem Menu system Grammar Lexicon Parser Dialogue Controller Conceptual Ontology Communication Manager Application

  27. The grammar and lexicon • They are obtained from the LO objects • They are represented in the definite-clause grammar (DCG) formalism because: • Definite-clause grammars are more expressive than conventional context-free grammars • They can be efficiently parsed • They are automatically generated

  28. The lexicon A lexical entry representing the verbser String Category Interpretation es verbser (syn(num(s),tense(p))) (((l,X),(l,Y)),(X,Y)) syntactic number singular tense present

  29. The lexicon A lexical entry representing the concept ARCHITECT un_arquitecto • String • Category • Semantic Interpretation indefngcon (syn(gen(m),num(s)), sem(con(architect))) syntactic gender masculine number singular semantic concept architect architect

  30. The lexicon Dynamic entries Representing instances of concepts Category function pngi(sem(con(person))) instance_of(person) Representing values of attributes requested to the user during communication Category function defngattrof(sem(con(person), attr(name))) name Representing all possible values of an attribute defngvalofcause(sem(con(requirementobuild),attr(reasonotbuilt))) menu(reasonotbuilt)

  31. The lexicon Dynamic entries • The number of lexical entries to be considered is reduced • They allow the introduction of new values during communication • They guide the user to introduce specialized terms

  32. The parser • It is based on the Ross version of the Left-corner algorithm • It assures there is always a correct choice to continue from a correct prefix (prefix correctness) • It can parse • A word and predicts the set of all possible next words

  33. The Dialogue Controller (DC) • The DC completes and disambiguates the semantic interpretation of the user request • The result is a complete specification of an operation over the Conceptual Ontology • The DC controls the execution of the operation • The DC passes the resulting information to the interface

  34. The Dialogue Controller • The DC completes and disambiguates the semantic interpretation of the user request using: • History of dialogue • Concept and parameters of the previous operations • The Conceptual Ontology • The definition of the operation: mandatory arguments, default values,... • This process is simple when users build the requests using the NL options shown in the screen • Mistakes and misunderstandings are avoided

  35. Applications of GISE SIREDOJ, an expert system in law • Previously its communicative tasks • were fully integrated with functional tasks • were based on a set of menus • Applying GISE improves the communication: • Complex concepts can be expressed in one sentence • User-initiative dialogues are allowed • The size of the linguistic resources is not big: 26 grammar rules and 112 lexical entries

  36. Conclusions • Main contribution: • Proposing an organization of the knowledge involved in communication that improves the obtaining of the linguistic resources most appropriate for each application

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

  38. Conclusions Proposing a reusable organization • The Linguistic Ontology • It is an adaptation of NIGEL grammar for communication with KBSs in Spanish • The Control Rules • They control the process of adapting linguistic knowledge to each application • A basic set of rules controls this process for different types of applications

  39. Conclusions Improving the NL processing Using grammars and lexicon restricted to the application communication tasks • Their size is not large: The parsing is simple • Dynamic categories are used • A menu-system is integrated in the NLI • They incorporate information from the Conceptual Ontology: The interpretation is simple • In the lexical entries • In the features augmenting the categories • In the preconditions associated with the rules

  40. Conclusions Improving communication and user satisfaction • Using an easy and clear language • Guiding the user about application specific information • Using a menu-system to introduce NL • The user is guided about the system requirements • The user can avoid typing sentences • Tools helping the user are incorporated into the interface

  41. GIWEB Interface User Grammar Lexicon Parser Conceptual Ontology Dialogue Controller Wrapper1 Wrapper2 Wrappern Internet Source1 Source2 Sourcen

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