Towards a Sensorimotor WordNet SM : Closing the Semantic Gap

We have empirically discovered that the space of human actions has a grammatical structure. This is a motoric space consisting of the evolution of the joint angles of the human body in movement. Furthermore, the process of assembling individual human movements into higher level descriptions resembles in a natural sense the process of speech recognition. Thus the space of human activity has its own phonemes, morphemes, words (verbs, nouns, adjectives, adverbs), and sentences formed by its own syntax. This has a number of implications for the grounding problem and cognition in general. With regard to WordNet, the theory points to a future Sensorimotor WordNet which contains a map between the nodes of the current WordNet and the space consisting of human action. In this paper, we suggest initial steps towards closing the semantic gap by grounding language with visuomotor information. The grounding takes place on a set of primitive words which are selected here through verb classification of the WordNet lexicon. A formal approach to the identification of primitive words would consider the basic atoms of WordNet extensions. However, one further extension is required to incorporate grounded information into WordNet in the direction of a sensorimotor WordNet, designated here as WordNet SM .

[1]  J. Gibson The Ecological Approach to Visual Perception , 1979 .

[2]  George A. Miller,et al.  WordNet 2 - A Morphologically and Semantically Enhanced Resource , 1999 .

[3]  Suzanne Stevenson,et al.  Automatic Verb Classification Based on Statistical Distributions of Argument Structure , 2001, CL.

[4]  W. K. Yeap On Symbol Grounding , 1993 .

[5]  Aldo Gangemi,et al.  The OntoWordNet Project: Extension and Axiomatization of Conceptual Relations in WordNet , 2003, OTM.

[6]  Deb Roy,et al.  Semiotic schemas: A framework for grounding language in action and perception , 2005, Artif. Intell..

[7]  Gutemberg Guerra-Filho,et al.  Optical Motion Capture: Theory and Implementation , 2005, RITA.

[8]  Jeffrey Mark Siskind,et al.  Grounding the Lexical Semantics of Verbs in Visual Perception using Force Dynamics and Event Logic , 1999, J. Artif. Intell. Res..

[9]  Mario Jino,et al.  Experimental Results from Application of Fault-Sensitive Testing Strategies , 2005, RITA.

[10]  Suzanne Stevenson,et al.  A General Feature Space for Automatic Verb Classification , 2003, EACL.

[11]  Y. Aloimonos,et al.  Discovering a Language for Human Activity 1 , 2005 .

[12]  H. Knecht A Taxonomy of the Psychomotor Domain: A Guide for Developing Behavioral Objectives , 1974 .

[13]  Roberto Basili,et al.  An Empirical Symbolic Approach to Natural Language Processing , 1996, Artif. Intell..

[14]  김두식,et al.  English Verb Classes and Alternations , 2006 .

[15]  Barbara B. Levin,et al.  English verb classes and alternations , 1993 .

[16]  Jerome A. Feldman,et al.  Extending Embodied Lexical Development , 1998 .

[17]  G. Miller,et al.  Semantic networks of english , 1991, Cognition.

[18]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[19]  Chris Brew,et al.  Inducing German Semantic Verb Classes from Purely Syntactic Subcategorisation Information , 2002, ACL.

[20]  Stevan Harnad,et al.  Symbol grounding problem , 1990, Scholarpedia.