Wrapping Up Ling 575 Spoken Dialog Systems June
- Slides: 22
Wrapping Up Ling 575 Spoken Dialog Systems June 5, 2013
Roadmap Overview Distinctive factors in dialog: Human-human Human-computer Dialog components & dialog management Specialized topics: Detailed analysis of: Distinctive factors Techniques and applications Discussion: Trends, techniques, interrelations
Characteristics of Dialog Human-human: Multi-party interaction: Flexible turn-taking, mixed initiative Speech acts: Actions via speech, levels of interpretation Implicature: Grice’s maxims Cooperativity & closure: Grounding and levels of display Corrections, repairs, and confirmations
Characteristics of Dialog Human-computer – most deployed systems Multi-party interaction:
Characteristics of Dialog Human-computer – most deployed systems Multi-party interaction: Rigid silence-based turn-taking, system or “mixed” initiative Speech acts:
Characteristics of Dialog Human-computer – most deployed systems Multi-party interaction: Rigid silence-based turn-taking, system or “mixed” initiative Speech acts: Actions via speech: dialog acts, NLU Implicature:
Characteristics of Dialog Human-computer – most deployed systems Multi-party interaction: Rigid silence-based turn-taking, system or “mixed” initiative Speech acts: Actions via speech: dialog acts, NLU Implicature: Um… depends on dialog management, NLU Grounding:
Characteristics of Dialog Human-computer – most deployed systems Multi-party interaction: Rigid silence-based turn-taking, system or “mixed” initiative Speech acts: Actions via speech: dialog acts, NLU Implicature: Um… depends on dialog management, NLU Grounding: Confirmation: implicit/explicit: learned? Corrections, repairs: problematic Why?
Characteristics of Dialog Human-computer – most deployed systems Multi-party interaction: Rigid silence-based turn-taking, system or “mixed” initiative Speech acts: Actions via speech: dialog acts, NLU Implicature: Um… depends on dialog management, NLU Grounding: Confirmation: implicit/explicit: learned? Corrections, repairs: problematic Constrained by complexity, processing, speed, etc
Dialog System Components HMM-based ASR models NLU: call-routing, semantic grammars Dialog acts and recognition Dialog management: Finite-state Frame-based Voice. XML Information state Statistical dialog management Lots of examples!
Topics In-depth discussions: Computational approaches to make human-computer interaction more like human-human interaction Many issues raised in characterizing dialog: Multi-party
Topics In-depth discussions: Computational approaches to make human-computer interaction more like human-human interaction Many issues raised in characterizing dialog: Multi-party: multi-party interaction, turn-taking, initiative Grounding
Topics In-depth discussions: Computational approaches to make human-computer interaction more like human-human interaction Many issues raised in characterizing dialog: Multi-party: multi-party interaction, turn-taking, initiative Grounding: Miscommunication & repair, incremental processing Interpretation:
Topics In-depth discussions: Computational approaches to make human-computer interaction more like human-human interaction Many issues raised in characterizing dialog: Multi-party: multi-party interaction, turn-taking, initiative Grounding: Miscommunication & repair, incremental processing Interpretation: Reference, affect, subjectivity, personification, information structure, prosody Multi-modality Applications and issues: Tutoring, machine translation, information-seeking Non-native speech
Interconnections Apps: MT Tutoring Non-native Turntaking Affect Sentiment Info. Struct Reference Increment Prosody Initiative Persona Multi-party Multimodality Miscommu nication
Interconnections Apps: MT Tutoring Non-native Turntaking Affect Sentiment Info. Struct Reference Increment Prosody Initiative Persona Multi-party Multimodality Miscommu nication
Techniques & Sources of Information Range of techniques:
Techniques & Sources of Information Range of techniques: Deep processing, shallow processing, manual rules Machine learning:
Techniques & Sources of Information Range of techniques: Deep processing, shallow processing, manual rules Machine learning: Anything from decision trees to POMDPs Information sources:
Techniques & Sources of Information Range of techniques: Deep processing, shallow processing, manual rules Machine learning: Anything from decision trees to POMDPs Information sources: Acoustic, lexical, prosodic, timing, syntactic, semantic, pragmatic, etc Multimodal: gaze, gesture, etc Integration
Techniques & Sources of Information Range of techniques: Deep processing, shallow processing, manual rules Machine learning: Anything from decision trees to POMDPs Information sources: Acoustic, lexical, prosodic, timing, syntactic, semantic, pragmatic, etc Multimodal: gaze, gesture, etc Integration: Complex and varied Huge feature vectors, tandem models, blackboards, learned Substantial strides, but huge remaining challenges
Questions? Favorite topic? Most surprising result? Most obvious result? Most surprising gap?
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