Information Density and Linguistic Encoding (IDeaL)

We introduce IDeaL (Information Density and Linguistic Encoding), a collaborative research center that investigates the hypothesis that language use may be driven by the optimal use of the communication channel. From the point of view of linguistics, our approach promises to shed light on selected aspects of language variation that are hitherto not sufficiently explained. Applications of our research can be envisaged in various areas of natural language processing and AI, including machine translation, text generation, speech synthesis and multimodal interfaces.

[1]  Steven T Piantadosi,et al.  Word lengths are optimized for efficient communication , 2011, Proceedings of the National Academy of Sciences.

[2]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[3]  Eugene Charniak,et al.  Entropy Rate Constancy in Text , 2002, ACL.

[4]  R. Levy Expectation-based syntactic comprehension , 2008, Cognition.

[5]  Alice Turk,et al.  The Smooth Signal Redundancy Hypothesis: A Functional Explanation for Relationships between Redundancy, Prosodic Prominence, and Duration in Spontaneous Speech , 2004, Language and speech.

[6]  Frank Keller,et al.  Data from eye-tracking corpora as evidence for theories of syntactic processing complexity , 2008, Cognition.

[7]  M. Bar Predictions in the brain : using our past to generate a future , 2011 .

[8]  T. Florian Jaeger,et al.  Redundancy and reduction: Speakers manage syntactic information density , 2010, Cognitive Psychology.

[9]  K. Rayner,et al.  Effects of contextual constraint on eye movements in reading: A further examination , 1996, Psychonomic bulletin & review.

[10]  T Florian Jaeger,et al.  On language 'utility': processing complexity and communicative efficiency. , 2011, Wiley interdisciplinary reviews. Cognitive science.

[11]  Marta Kutas,et al.  CHAPTER 15 A Look around at What Lies Ahead: Prediction and Predictability in Language Processing , 2010 .

[12]  Jörg Hoffmann,et al.  Search Challenges in Natural Language Generation with Complex Optimization Objectives , 2015, KI - Künstliche Intelligenz.

[13]  S. Piantadosi,et al.  Info/information theory: Speakers choose shorter words in predictive contexts , 2013, Cognition.

[14]  Peter Fankhauser,et al.  The linguistic construal of disciplinarity: A data‐mining approach using register features , 2016, J. Assoc. Inf. Sci. Technol..

[15]  Claude E. Shannon,et al.  The mathematical theory of communication , 1950 .

[16]  John Hale,et al.  A Probabilistic Earley Parser as a Psycholinguistic Model , 2001, NAACL.

[17]  Nathaniel J. Smith,et al.  The effect of word predictability on reading time is logarithmic , 2013, Cognition.