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Human Act of Feedback ”When should I backchannel/barge-in?”

Human Act of Feedback ”When should I backchannel/barge-in?” . Ling575 Spoken Dialog Systems June 5 , 2013 Sanae Sato. Some Experiment…. Natural human-human conversation Three people / 60 min / roughly 970 sentences. Context: dinner table conversation

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Human Act of Feedback ”When should I backchannel/barge-in?”

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  1. Human Act of Feedback”When should I backchannel/barge-in?” Ling575 Spoken Dialog Systems June 5, 2013 Sanae Sato

  2. Some Experiment… • Natural human-human conversation • Three people / 60 min / roughly 970 sentences. • Context: dinner table conversation • Back-channeling/Barge-in are used quite effectively among human-to-human conversation. (= 3-5 % of conversation)

  3. Human Act of Feedback • From Observation… • Both backchannel and barge-ins plays important role for grounding purpose. Especially, Barge-in is extremely powerful for listener to keep track of topic/context. • Assumption1: Generating backchannelsis effective in term of grounding. • Assumption2: Similarly, generating effective barge-ins can lead to more beneficial interactions. • “Did you mean say Indian or Italian?”  Increase confd. Score • Another scenario: Reaction to barge-in  Yield of keep the turn? • Silence?: not considered for this project. • Question: When should I (or system) backchannel/barge-in?

  4. Main Topics to be Covered • Framework Model: • Dethlefset al. 2012“Optimising Incremental Dialogue Decisions Using Information Density for Interactive Systems” • Domain: Restaurant Recommendation Application • Information Presentation • Hierarchical Learning • Incremental Actions • Semi-Markov Decision Process (SMDP) • Slot-ordering & Confidence Score • …Good paper, but it lacks of human data!

  5. Main Topics to be Covered • Information Density (Jaeger 2010) • Dialogue Management • Turn-Taking • Data: • Dinner table conversation • CALLHOME (telephone speech corpus)

  6. References • Nina Dethlefs, Helen Hastie 2012 Optimising Incremental Dialogue Decisions Using Information Density for Interactive Systems. @ ACL 2012 • T. Florian Jaeger 2010 Redundancy and reduction: Speakers manage sysntactic information density. (Cognitive Psychology 61:23-62) • From Class Reading: • David Schlangen & Gabriel Skantze A General, Abstract Model of Incremental Dialogue Processing @ European ACL 2009 • Gabriel Skantze & David Schlangen:IncrementalDialgueProcessinginaMicro-Domain @ European ACL 2009 • David DeVault, Kenji Sage, and David Traum. 2009. Can I finish? Learning when to respond to incremental interpretations results in interactive dialogue. In Proc. SIGdial 2009 Conference, pages 11-20 • Ethan O. Selfridge, et al. 2011. Stability and accuracy in Incremental Speech Recognition

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