Advanced TuTalk Dialogue Agents

Advanced TuTalk Dialogue Agents Pamela Jordan University of Pittsburgh Learning Research and Development Center

Agenda • Introducing the TuTalk dialogue system server • System architecture (briefly) • Web interface to server for • Fielding experiments • Analyzing experiments • For uploading sc and xml directly to dialogue system server • Introduce additional authoring features • Enabling and controlling automated feedback • Optional steps (sc only) • Looping (sc only)

Architecture of TuTalk Dialogue System • Hub & spokes architecture • Main modules: • Coordinator • Language recognition • Language generation • Dialogue manager • Dialogue History database

Language recognition • Refers to labelled sets of alternative phrasings called concepts • Inputs from dialogue manager • normalized sentence, • set of expected response concepts • Computes minimum edit distance, number of adds and deletes of words needed to match input language to a concept • Returns expected response concept with smallest minimum edit distance that falls within a threshold

Language generation • Refers to labelled sets of alternative phrasings called concepts • Input from dialogue manager: a concept • If > 1 alternative phrasing, removes one last used according to dialogue history • Randomly selects from remaining alternative phrasings • Requests output of selected phrasing to student

Integrating TuTalk • Can integrate (embed/wrap) other modules • ProPL • Cordillera • Hub & spokes architecture • Replaceable modules e.g., NLU

Replaceable language modules • Replace: • Use a human (1 experiment) • Use another approach • Supplement: Human reviews and corrects choices made by recognition module (1 experiment)

Experiment management/analysis • Experiment management tools: http://pyrenees.lrdc.pitt.edu/~tutalk/cgi-bin/admin.cgi • One scenario/script = one dialogue agent = one condition, but can organize in other ways • One agent per unit • One agent that tells all knowledge components vs. one that elicits vs. one that uses a strategy to decide which to do • Condition management • Start on server and leave it running • Designate who is allowed in the condition • SQL database of information collected during interaction • Can download or query • Working on producing DataShop format

Setting up a scenario

SQL database access

Requesting a transcript

Transcript for a student

Additional authoring features • Automated turn transitions/feedback • Must specify truth-values for responses in context of an initiation • Default truth-value is “unknown” • Override automated turn transitions/feedbacks with a “say” • Optional steps: • Skip if specified condition met in recent dialogue history • Looping: • Repeat the template for a goal until a condition is met • Globally set condition once set

Script w/ truth-val in sc g select-appetizer say enthuse_about_appetizers say ask_share_appetizer if agree_to_share_appetizer if skip_appetizer true do “abort ask-soup” else do “abort lose-temper” do agree-on-appetizer

Automatically generated response feedback • “say” feature in authoring tool overrides automatic feedback • “say” following a response in sc overrides automatic feedback • Can globally enable/disable in xml configuration section (default is enabled)

Script w/ auto feedback override in sc g select-appetizer say enthuse_about_appetizers say ask_share_appetizer if agree_to_share_appetizer if skip_appetizertrue say “Okay, in that case I won’t get an appetizer.” do “abort ask-soup” else do “abort lose-temper” do agree-on-appetizer

Authoring response feedback (1)

Authoring response feedback (2)

As a runner pushes a ball away, what horizontal forces act on it? Good! <subdialog> <subdialog > Any others? Any others? After the push ends, what forces….? Optional Steps {gravitational, *} {runner’s} <anything else> not said said

Example of optional steps T: … what horizontal forces are acting on it while she is pushing it? S: Gravity? T: In what direction does gravity act? . T: So are there any other forces on the ball? S: no T: What about the runner? . T: Okay. After the push ends, what forces… subdialogue T: … what horizontal forces are acting on it while she is pushing it? S: The runner’s T: Right! So are there any other forces on the ball? S: no T: Good. After the push ends, what forces…

Script with an optional step and semantic labels in sc g ask-appetizer say enthuse-about-appetizers opt sem enthuse-about-appetizers say ask-appetizer if skip-appetizer sem skip-appetizer-order do “abort soup” if no do “abort soup” else do lose-temper do order-appetizer

Looping for a dialogue • Continuous loop on a template: repeat template until all indicated components covered T: Okay, great. What should we work on now? S: Add a loop T: That’s right. We will have to add a loop. Let’s figure out why. What made you think of using a loop? S: . . T: Okay. What should we work on now? . . T: So, with that we’re finished with this problem. (example based on Lane 04)

Script with a loop and semantic labels in sc g start do 76 do 36 do 163 do 58 g 76 loop finished76 say the-first-problem-will-take-about do prob76 say the-next-problem-will-take-about-3 sem finished76 if yes else do logout-msg

Configuration section in sc format config global version "$Revision: 1.75 $" default-language en # We use several proper nouns in the scenario, so we declare them here, and provide # morphological info so en-normalizer.py won’t spell-correct them. A different # normalizer will probably require (and hopefully document) a different format. config normalizer lexicon-supplement "Python{’en’: [’springfield n-springfield-’, ’chicago n-chicago-’, ’ontario n-ontario-’, ’illinois n-illinois-’, ’superior n-superior-’, ’huron n-huron-’, ’erie n-erie-’, ’michigan n-michigan-’, ’ontario n-ontario-’ ]}"

Advanced TuTalk Dialogue Agents