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RavenClaw Yet another (please read “An improved”) dialog management architecture for task-oriented spoken dialog systems Presented by: Dan Bohus (dbohus@cs.cmu.edu) Work by: Dan Bohus, Alex Rudnicky Carnegie Mellon University, 2002
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11-04-01Modeling the cost of misunderstanding …2 New DM Architecture: Goals Able to handle complex, goal-directed dialogs Go beyond (information access systems and) the slot-filling paradigm Easy to develop and maintain systems Developer focuses only on dialog task Automatically ensure a minimum set of task- independent, conversational skills Open to learning (hopefully both at task and discourse levels) Open to dynamic SDS generation More careful, more structured code, logs, etc: provide a robust basis for future research.
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11-04-01Modeling the cost of misunderstanding …3 A View from far, far away What did you just say ? What’s your name ? SELECT * WHERE … Since that failed, I need you to push button B Can you repeat that, please ? Suspend… Resume … Conversational Skills Dialog Task Specification Backend Core Let the developer focus only on the dialog task spec.: Don’t worry about misunderstandings, repeats, focus shift, etc… merely describe (program) the task, assuming perfect knowledge of the world Automatically generate the conversational mechanisms Examples
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11-04-01Modeling the cost of misunderstanding …4 Outline Goals A view from far away Main ideas Dialog Task Specification / Execution Conversational skills In more detail Dialog Task Specification / Execution Conversational skills Conversational DTS Backend Core
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11-04-01Modeling the cost of misunderstanding …5 Dialog Task Spec & Execution Communicator Welcome LoginTravelLocals Bye AskRegistered AskName GreetUserGetProfile Leg1 DepartLocationArriveLocation Agencies and Microagents (for input, request, execute …) Handle Concepts Execution with interleaved Input Passes. Execute the agents by top-down “planning” Do input passes when information is required REMEMBER: This is just the dialog task
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11-04-01Modeling the cost of misunderstanding …6 Handling inputs Communicator Welcome LoginTravelLocals Bye AskRegistered AskName GreetUserGetProfile Leg1 DepartLocationArriveLocation Input Pass Assemble an agenda of expectations (open concepts) Bind values from the input to the concepts Process non-understanding (if), analyze need for focus shifts Continue execution
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11-04-01Modeling the cost of misunderstanding …7 Conversational Skills / Mechanisms A lot of problems in SDS generated by lack of conversational skills. “It’s all in the little details!” Dealing with misunderstandings Generic channel/dialog mechanisms : repeats, focus shift, context establishment, help, start over, etc, etc. Timing Even when these mechanisms are in, they lack uniformity & consistency. Development and maintenance are time consuming.
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11-04-01Modeling the cost of misunderstanding …8 Conversational Skills / Mechanisms More or less task independent mechanisms: Implicit/Explicit Confirmations, Clarifications, Disambiguation = the whole Misunderstandings problem Context reestablishment Timeout and Barge-in control Back-channel absorption Generic dialog mechanisms: Repeat, Suspend… Resume, Help, Start over, Summarize, Undo, Querying the system’s belief The core takes care of these by dynamically inserting in the task tree agencies which handle these mechanisms.
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11-04-01Modeling the cost of misunderstanding …9 Outline Goals A view from far away Main ideas Dialog Task Specification / Execution Conversational skills In more detail Dialog Task Specification / Execution Conversational skills Conversational DTS Backend Core
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11-04-01Modeling the cost of misunderstanding …10 Dialog Task Specification Goal: able to handle complex domains, beyond information access, frame-based, slot-filling systems i.e. : Symphony, Intelligent checklists, Navigation, Route planning We need a powerful enough formalism to describe all these tasks: C++ code ? Declarative would be nice … but is it powerful enough ? Templatized C++ code … ?
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11-04-01Modeling the cost of misunderstanding …11 Dialog Task Specification A possible more formalized approach Tree of agents with: Preconditions Success Criteria Focus Criteria (triggers) Expressed mostly in terms of concepts Data, Type (basic, struct, array) Confidence, Availability, Ambiguousness, Groundedness, System/User, TurnAcquired, TurnConveyed, etc…
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11-04-01Modeling the cost of misunderstanding …12 An example DTS UserLogin: AGENCY concepts: registered(BOOL), name(STRING), id(STRING), profile(PROFILE), profile_found(BOOL) achieves_when: profile || InformProfileNotFound AskRegistered: REQUEST(registered) grammar: {[yes]->true,[no]->false,[guest]->false} AskName: REQUEST(name) precond: registered==no grammar: [user_name] max_attemps: 2 InformGreetUser: INFORM precond: name AskID: REQUEST(id) precond: registered==yes mapping: [user_id] DoProfileRetrieval: EXECUTE precond: name || id call: ABEProfile.Call >name, >id, <profile, <profile_found InformProfileNotFound: INFORM precond: !profile_found Given that the baseline is 259 lines of C++ code, this is pretty good.
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11-04-01Modeling the cost of misunderstanding …13 Can a formalism cut it ? People have repeatedly tried formalizing dialog … and failed We’re focusing only on the task (like in robotics/execution) Actually, these agents are all C++ classes, so we can backoff to code; the hope is that most of the behaviors can be easily expressed as above.
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11-04-01Modeling the cost of misunderstanding …14 Other Ideas for DTS 4 Microagents: Inform, Request, Expect, Execute Provide a library of “common task” and “common discourse” agencies Frame agency List browse agency Choose agency Disambiguate agency, Ground Agency, … Etc
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11-04-01Modeling the cost of misunderstanding …15 DTS execution Agency.Execute() decides what is executed next Various simple policies can be implemented Left-to-right (open/closed), choice, etc But free to do more sophisticated things (MDPs, etc) ~ learning at the task level
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11-04-01Modeling the cost of misunderstanding …16 Input Pass 1. Construct an agenda of expectations (Partially?) ordered list of concepts expected by the system 2. Bind values/confidences to concepts The SI <> MI spectrum can be expressed in terms of the way the agenda is constructed and binding policies, independent of task 3. Process non-understandings (iff) - try and detect source and inform user: Channel (SNR, clipping) Decoding (confidence score, prosody) Parsing ([garble]) Dialog level (POK, but no expectation)
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11-04-01Modeling the cost of misunderstanding …17 Input Pass 4. Focus shifts Focus shifts seem to be task dependent. Decision to shift focus is taken by the task (DTS) But they also have a TI-side (sub-dialog size, context reestablishment). Context reestablishment is handled automatically, in the Core (see later)
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11-04-01Modeling the cost of misunderstanding …18 Outline Goals A view from far away Main ideas Dialog Task Specification / Execution Conversational skills In more detail Dialog Task Specification / Execution Conversational skills Conversational DTS Backend Core
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11-04-01Modeling the cost of misunderstanding …19 Task-Independent, Conversational Mechanisms Should be transparently handled by the core; little or no effort from the developer However, the developer should be able to write his own customized mechanisms if needed Handled by inserting extra “discourse” agents on the fly in the dialog task specification
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11-04-01Modeling the cost of misunderstanding …20 Conversational Skills Universal dialog mechanisms: Repeat, Suspend… Resume, Help, Start over, Summarize, Undo, Querying the system’s belief The grounding / misunderstanding problems Timing and Barge-in control Focus Shifts, Context Establishment Back-channel absorption Q: To which extent can we abstract these away from the Dialog Task ?
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11-04-01Modeling the cost of misunderstanding …21 Repeat Repeat (simple) The DTT is adorned with a “Repeat” Agency automatically at start-up Which calls upon the OutputManager Not all outputs are “repeatable” (i.e. implicit confirms, gui, )… which ones exactly… ? Repeat (with referents) only 3%, they are mostly [summarize] User-defined custom repeat agency
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11-04-01Modeling the cost of misunderstanding …22 Help DTT adorned at start-up with a help agency Can capture and issue: Local help (obtained from focused agent) ExplainMore help (obtained from focused) What can I say ? Contextual help (obtained from main topic) Generic help (give_me_tips) Obtains Help prompts from the focused agent and the main topic (defaults provided) Default help agency can be overwritten by user
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11-04-01Modeling the cost of misunderstanding …23 Suspend … Resume DTT adorned with a SuspendResume agency. Forces a context reestablishment on the current main topic upon resume. Context reestablishment also happens when focusing back after a sub-dialog Can maybe construct a model for that (given size of sub-dialog, time issues, etc)
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11-04-01Modeling the cost of misunderstanding …24 Start over, Summarize, Querying Start over: DTT adorned with a Start-Over agency Summarize: DTT adorned with a Summarize agency; prompt generated automatically, problem shifted to NLG: can we do something corpus- based … work on automated summarization ? Querying the system’s beliefs: Still thinking… problem with the grammars… can meaningful Phoenix grammars for “what is [slot]” be automatically generated ?
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11-04-01Modeling the cost of misunderstanding …25 Timing & barge-in control Knowledge of barge-in location Information on what got conveyed is fed back to the DM, through the concepts to the task level Special agencies can take special action based on that (I.e. List Browsing) Can we determine what are non-barge-in-able utterances in a TI manner ?
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11-04-01Modeling the cost of misunderstanding …26 Confirmation, Clarif., Disamb., Misunderstandings, Grounding… Largely unsolved in my head: this is next ! 2 components: Confidence scores on concepts Obtaining them Updating them Taking the “right” decision based on those scores: Insert appropriate agencies on the fly in the dialog task tree: opportunity for learning What’s the set of decisions / agencies ? How does one decide ?
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11-04-01Modeling the cost of misunderstanding …27 Confidence scores Obtaining conf. Scores : from annotator Updating them, from different sources: (Un)Attacked implicit/explicit confirms Correction detection Elapsed time ? Domain knowledge Priors ? But how do you integrate all these in a principled way ?
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11-04-01Modeling the cost of misunderstanding …28 Mechanisms DepartureCity = Implicit / Explicit confirmations When do you leave from Seattle ? So you’re leaving from Seattle… When ? Clarifications Did you say you were leaving from Seattle ? Disambiguation I’m sorry was that Seattle or San Francisco? How do you decide which ? Learning ?
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11-04-01Modeling the cost of misunderstanding …29 Software Engineering Provide a robust basis for future research. Modularity Separability between task and discourse Separability of concepts and confidence computations Portability Mutiple servers Aggressive, structured, timed logging
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