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Introduction to the TrindiKit

Introduction to the TrindiKit. Dialogue Systems 2 GSLT spring 2003 Staffan Larsson sl@ling.gu.se. What is TrindiKit?. a toolkit for building and experimenting with dialogue move engines and systems, based on the information state approach not a dialogue system!. This lecture.

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Introduction to the TrindiKit

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  1. Introduction to the TrindiKit Dialogue Systems 2 GSLT spring 2003 Staffan Larsson sl@ling.gu.se

  2. What is TrindiKit? a toolkit for building and experimenting with dialogue move engines and systems, based on the information state approach not a dialogue system!

  3. This lecture • architecture & concepts • what’s in TrindiKit? • extending TrindiKit • building a system

  4. Architecture & concepts

  5. control DME module1 module… modulei modulej module… modulen • Total Information State • (TIS) • Information state proper (IS) • Module Interface Variables • Resource Interface Variables resource1 resource… resourcem

  6. Information State (IS) • an abstract data structure (record, DRS, set, stack etc.) • accessed by modules using conditions and operations • the Total Information State (TIS) includes • Information State proper (IS) • Module Interface variables • Resource Interface variables

  7. Dialogue Move Engine (DME) • module or group of modules responsible for • updating the IS based on observed moves • selecting moves to be performed • dialogue moves are associated with IS updates using IS update rules • there are also update rules no directly associated with any move (e.g. for reasoning and planning) • update rules: rules for updating the TIS • rule name and class • preconditon list: conditions on TIS • effect list: operations on TIS • update rules are coordinated by update algorithms

  8. Modules and resources • Modules (dialogue move engine, input, interpretation, generation, output etc.) • access the information state • no direct communication between modules • only via module interface variables in TIS • modules don’t have to know anything about other modules • increases modularity, reusability, reconfigurability • may interact with user or external processes • Resources (device interface, lexicons, domain knowledge etc.) • hooked up to the information state (TIS) • accessed by modules • defined as object of some type (e.g. ”lexicon”)

  9. What’s in TrindiKit?

  10. What does TrindiKit provide? • High-level formalism and interpreter for implementing dialogue systems • promotes transparency, reusability, plug-and-play, etc. • allows implementation and comparison of dialogue theories • hides low-level software engineering issues • GUI, WWW-demo • Ready-made modules and resources • speech • interfaces to databases, devices, etc. • reasoning, planning

  11. TrindiKit contents (1) • alibrary of datatype definitions (records, DRSs, sets, stacks etc.) • user extendible • alanguage for writing information state update rules • GUI: methods and tools for visualising the information state • debugging facilities • typechecking • logs of communication modules-TIS • etc.

  12. TrindiKit contents (2) • A language for defining update algorithms used by TrindiKit modules to coordinate update rule application • A language for defining basic control structure, to coordinate modules • A library of basic ready-made modules for input/output, interpretation, generation etc.; • A library of ready-made resources and resource interfaces, e.g. to hook up databases, domain knowledge, devices etc.

  13. Special modules and resources included with TrindiKit • OAA interface resource • enables interaction with existing software and languages other than Prolog • Speech recognition and synthesis modules • TrindiKit shells for off-the-shelf recognisers • currently only ViaVoice, but more on the way • Possible future modules: • planning and reasoning modules • multimodal input and output

  14. Asynchronous TrindiKit • Internal communication uses either • OAA (Open Agent Architecture) from SRI, or • AE (Agent Environment), a stripped-down version of OAA, implemented for TrindiKit • enables asynchronous dialogue management • e.g.: system can listen and interpret, plan the dialogue, and talk at the same time

  15. How to build a system

  16. How to use TrindiKit We start from TrindiKit Implements the information state approach Takes care of low-level programming: dataflow, datastructures etc. TrindiKit information state approach

  17. How to build a basic system Formulate a basic dialogue theory Information state Dialogue moves Update rules Add appropriate modules (speech recognition etc) basic dialoguetheory basic system TrindiKit information state approach

  18. How to build a genre-specific system Add genre-dependent IS components, moves and rules genre-specific theory additions genre-specific system basic dialoguetheory basic system TrindiKit information state approach

  19. How to build an application Add application-specific resources application domain & language resources genre-specific theory additions genre-specific system basic dialoguetheory basic system TrindiKit information state approach

  20. Building a domain-independent Dialogue Move Engine • Come up with a nice theory of dialogue • Formalise the theory, i.e. decide on • Type of information state (DRS, record, set of propositions, frame, ...) • A set of dialogue moves • Information state update rules, including rules for integrating and selecting moves • DME Module algorithm(s) and basic control algorithm • any extra datatypes (e.g. for semantics: proposition, question, etc.)

  21. Domain independence of the Dialogue Move Engine • The DME is domain independent, given a certain type of dialogue • information-seeking • instructional • negotiative • ... • Domain independence of DME is not enforced by TrindiKit, but is good practice • promotes reuse of components • forces abstraction from domain-specific details, resulting in a more general theory of dialogue

  22. Specifying Infostate type • the Total Information State contains a number of Information State Variables • IS, the Information State ”proper” • Interface Variables • used for communication between modules • Resource Variables • used for hooking up resources to the TIS, thus making them accessible from to modules • use prespecified or new datatypes

  23. sample infostate type declaration infostate_variable_of_type( is, IS ) :- IS = record( [ private : Private, shared : Shared ] ), Shared = record( [ com : set( proposition ), qud : stack( question ), lm : set( move ) ] ), Private = record( [ agenda: stack( action ), plan : stackset( action ), bel : set( proposition ), tmp : Shared ] ) ] ).

  24. resulting infostate type AGENDA : stack( Action ) PLAN : stackset( Action ) PRIVATE : BEL : set( Prop ) TMP : (same type as SHARED) COM : set( Prop ) QUD : stack( Question ) SHARED : LU: [SPEAKER:dp, MOVES:set( Move )]

  25. Sample interface variable type declarations interface_variable_of_type( input, string ). interface_variable_of_type( output, string ). interface_variable_of_type( latest_speaker, speaker ). interface_variable_of_type( latest_moves, set(move) ). interface_variable_of_type( next_moves, set(move) ).

  26. Specifying a set of moves • amounts to specifying objects of type move (a reserved type) • there may be type constraints on the arguments of moves • preconditions and effects of moves • formalised in update rules, not in the move definition itself • a move may have different effects on the IS depending e.g. on who performed it

  27. sample move specifications % Social of_type( quit, move ). of_type( greet, move ). of_type( thank, move ) . % Q&A of_type( ask(Q), move ) <- of_type( Q, question ). of_type(inform(P), move ) <- of_type( P, proposition). of_type( answer(R), move ) <- of_type( R, proposition) or of_type( R, ellipsis ).

  28. Writing rules • rule = conditions + updates • if the rule is applied to the IS and its conditions are true, the operations will be applied to the IS • conditions may bind variables with scope over the rule (prolog variables, with unification and backtracking)

  29. A sample rule rule( integrateUsrAnswer, [ $/shared/lu/speaker = usr, assoc( $/shared/lu/moves, answer(R), false ), fst( $/shared/qud, Q ), $domain : relevant_answer( Q, R ), $domain : reduce(Q, R, P) ], [ set_assoc( /shared/lu/moves, answer(R),true), shared/qud := $$pop( $/shared/qud ), add( /shared/com, P ) ] ).

  30. A sample rule (old syntax) • rule( integrateUsrAnswer, [ • val#rec( shared^lu^speaker, usr ), • assoc#rec( shared^lu^moves, answer( R ), false ), • fst#rec( shared^qud, Q ), • domain :: relevant_answer( Q, R ), • domain :: reduce(Q, R, P) • ], [ • set_assoc#rec( shared^lu^moves, answer(R),true), • pop#rec( shared^qud ), • add#rec( shared^com, P ) ] ).

  31. Writing rules • available conditions and operations depend on the infostate type • the infostate is declared to be of a certain (usually complex) type • datatype definitions provide • selectors: Sel(InObj,SelObj) • relations:Rel(Arg1, …, ArgN) • functions:Fun(Arg1, …, ArgN,Result) • operations: Op(ObjIn,Arg1, …, ArgN,ObjOut) • New datatypes may be added

  32. Writing rules: locations in TIS • objects may be specified by giving a path to a locationin the infostate; • paths are specified using selectors, which are similar to functions • $$Sel2($$Sel1) ~ $Sel1/Sel2 • $$fst($/shared/qud) ~ $/shared/qud/fst • ”$” evaluates a path and gives the object at the location specified • ”$$” evaluates a function • $$fst($/shared/qud) = $/shared/qud/fst • example: • is/shared/com is a path, pointing to a location in the TIS • $is/shared/com is the object in that location • theiscan be left out, giving$/shared/com

  33. Writing rules: conditions (1) • conditions do not change the information state • if a condition fails, backtracking ensues • condition syntax (incomplete) • Rel(Arg1, … , ArgN), e.g. • fst($/shared/qud,Q) • Arg1:Rel(Arg2,…,ArgN), e.g. • $/shared/qud:fst(Q) • $domain:relevant_answer(Q,A) • Arg1 = Arg2 • Q = $$fst($/shared/qud) • Cond1 and Cond2 • Cond1 or Cond2 • not Cond1 • forall(Cond1, Cond2) • (Argis object or prolog variable)

  34. Writing rules: conditions (2) • quantification, binding and backtracking • if an instantiation a of a variable V in a condition C is found that makes condition C true, V is bound to a • backtracking occurs until a successful instantiation of all variables in the list of conditions has been found • example list of conditions fst($/shared/qud,Q), in($/shared/com,P), $domain:relevant_answer(P,Q) • Explicit quantification Q.P. fst($/shared/qud,Q) & in($/shared/com,P) & $domain:relevant_answer(P,Q)

  35. Writing rules: updates • operations change the information state • if an operation fails, an error is reported • variable bindings survive from conditions to operations • operation syntax (incomplete) • Op(Path,Arg1,…,ArgN) • push(/shared/qud, Q) • Path : Op(Arg1, … ,ArgN) • /shared/qud : push(Q) • Store := Fun(Obj,Arg1,…,ArgN) • /private/tmp/qud := $$push($/shared/qud,Q)

  36. Specifying update algorithms • uses rule classes • constructs include • Rule • RuleClass • if Cond then S else T • repeat R until C • repeat R • try R • R orelse S • test C • SubAlgorithm

  37. Sample update algorithm grounding, if $latest_speaker == sys then try integrate, try database, repeat downdate_agenda, store else repeat integrate orelse accommodate orelse find_plan orelse if (empty ( $/private/agenda ) then manage_plan else downdate_agenda repeat downdate_agenda if empty($/private/agenda)) then repeat manage_plan repeat refill_agenda repeat store_nim try downdate_qud

  38. Specifying serial control algorithms • serial constructs include • Module{:Algorithm} • if Cond then S else T • repeat R until C • repeat R • try R • R orelse S • test C • SubAlgorithm

  39. Specifying concurrent control algorithms • Agent1 | Agent2 | … | AgentN • whereAgenti is • AgentName : { • import Module1 , • … • import Modulep , • Trigger1 => SerialAlgoritm1 , • … • Triggerm => SerialAlgoritmm } • triggers: • condition(C) (C is a subset of the full condition set) • init • new_data(Stream)

  40. Sample control algorithm (1) repeat ( [ select, generate, output, update, test( $program_state == run ), input, interpret, update ] )

  41. Sample control algorithm (2) input: { init => input:display_prompt, new_data(user_input) => input } | interpretation: { import interpret, condition(is_set(input)) => [ interpret, print_state ] } | dme: { import update, import select, init => [ select ], condition(not empty(latest_moves)) => [ update, if $latest_speaker == usr then select ] } | generation: { condition(is_set(next_moves)) => generate } | output: { condition(is_set(output)) => output } )).

  42. From DME to dialogue system Build or select from existing components: • Modules, e.g. • input • interpretation • generation • output • Still domain independent • the choice of modules determines e.g. the format of the grammar and lexicon

  43. Domain-specific system Build or select from existing components: • Resources, e.g. • domain (device/database) interface • dialog-related domain knowledge, e.g. plan libraries etc. • grammars, lexicons

  44. Extending TrindiKit

  45. You can add • Datatypes • Whatever you need • Modules • e.g. General interfaces to speech recognizers and synthesizers • Resources • E.g. General interfaces to (passive) devices • Important that all things added are reasonably general, so they can be reused in other systsems

  46. Datatype definitions • relations • relations between objects; true or false • format: relation(Rel,Args). • Example • definition: relation(fst,[stack([E|S]),E]). • condition: fst($/shared/qud,Q)

  47. Datatype definitions • functions • functions from arguments to result • format: function(Fun,Args,Result). • Example • definition: function(fst,[stack([E|S])],E). • in condition: • Q = $$fst($/shared/qud) • Q = $/shared/qud/fst • in effect: • next_move/content := $$fst($/shared/qud) • every function corresponds to a relation relation(Fun,[Args@[Result]]).

  48. Datatype definitions (2) • selectors • selects an object (Obj) embedded in another object (Arg) • selector(Sel,Arg,Obj,ArgWithHole,Hole). • e.g. selector(fst,stack([E|S]),E,stack([H|S]),H). • Every selector corresponds to a function function(Sel,[Arg],Object).

  49. Datatype definitions (3) • operations • operation(Op,InObj,Args,OutObj). • e.g. operation(push,stack(S),[E],stack([E|S])). • every operation corresponds to a relation relation(Op,[InObj|Args]@[OutObj]). • push($/shared/qud,Q,$/shared/qud).

  50. Building modules • DME modules • Specific to a certain theory of dialogue management • Best implemented using rules and algorithms • Other modules • Should be more general, less specific to certain theory of dialogue management • May be easier to implement directly in prolog or other language • DME-ADL only covers checking and updating the infostate • These modules may also need to interact with other programs or devices

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