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Unifying Language Modeling for Flexible Human-Computer Interaction

This paper presents a comprehensive framework for unifying language modeling capabilities to enhance flexible interactions in human-computer interfaces. Authors Deryle Lonsdale and Rebecca Madsen explore the integration of Soar cognitive modeling systems with natural language components to enable goal-directed communication. Key topics include incremental comprehension and generation modeling, X-bar syntax, LCS semantics, and discourse modeling techniques. The framework utilizes tools such as Sphinx for speech recognition and Festival TTS for dialogue processing, applicable in scenarios ranging from HCI to agent-based communication.

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Unifying Language Modeling for Flexible Human-Computer Interaction

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  1. Unifying language modeling capabilities for flexible interaction Deryle Lonsdale & Rebecca Madsen lonz@byu.edu, rmadsen@byu.net Interspeech DoD 2006

  2. Language modeling capabilities • Soar cognitive modeling system • Goal-directed, operator-based production system with machine learning • Natural-language components • Incremental comprehension modeling • Incoming words  X-bar syntax  LCS semantics • Incremental generation modeling • LCS semantics  X-bar syntax  outgoing words • Opportunistic discourse modeling • Recipes: flexible plan recognition/formulation • Speech input/output • Sphinx recognizer, Festival TTS

  3. Dialogue plan recognition/formulation

  4. Scenarios: HCI, agentagent

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