Robot acquisition of lexical meaning - moving towards the two-word stage

We report on experiments and analyses dealing with the acquisition of lexical meaning in which prosodic analysis and extraction of salient words are associated with a robots sensorimotor perceptions in an attempt to ground these words in the robots own embodied sensorimotor experience. We focus here on three key areas, the selection of salient words based on prosodic clues, expression of words by the robot at a two-word stage to reflect learning and grammatically correct presentation, and an in-depth analysis of the relationship between words and the robots sensorimotor perceptions.

[1]  Helen Goodluck,et al.  First language acquisition. , 2011, Wiley interdisciplinary reviews. Cognitive science.

[2]  Kerstin Fischer,et al.  Tutor Spotter: Proposing a Feature Set and Evaluating It in a Robotic System , 2011, International Journal of Social Robotics.

[3]  Chrystopher L. Nehaniv Meaning for observers and agents , 1999, Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014).

[4]  Charles A. Ferguson,et al.  Model-and-replica phonological grammar of a child's first words , 1973 .

[5]  Evena Wong,et al.  Pragmatic directions about language use: Offers of words and relations , 2002, Language in Society.

[6]  C. A. Ferguson,et al.  Talking to Children: Language Input and Acquisition , 1979 .

[7]  P. Bloom How Children Learn the Meaning of Words and How LSA Does It ( Too ) , 2005 .

[8]  Chrystopher L. Nehaniv,et al.  Robots That Say 'No' , 2009, ECAL.

[9]  P. Broen,et al.  The Verbal Environment of the Language-Learning Child. ASHA Monographs, No. 17. , 1972 .

[10]  A. Fernald,et al.  Prosody and focus in speech to infants and adults , 1991 .

[11]  Chrystopher L. Nehaniv,et al.  Robot learning of lexical semantics from sensorimotor interaction and the unrestricted speech of human tutors , 2010 .

[12]  D. Roy Grounding words in perception and action: computational insights , 2005, Trends in Cognitive Sciences.

[13]  Alberto Maria Segre,et al.  Programs for Machine Learning , 1994 .

[14]  Mark Steyvers,et al.  Online Learning Mechanisms for Bayesian Models of Word Segmentation , 2010 .

[15]  Kerstin Dautenhahn,et al.  Self-Imitation and Environmental Scaffolding for Robot Teaching , 2007 .

[16]  Kerstin Fischer,et al.  Contingency allows the robot to spot the tutor and to learn from interaction , 2011, 2011 IEEE International Conference on Development and Learning (ICDL).

[17]  Gabriel Furmuzachi,et al.  WORDS AND THINGS , 1906, British medical journal.

[18]  Mary P. Harper,et al.  An Open Source Prosodic Feature Extraction Tool , 2006, LREC.

[19]  Chrystopher L. Nehaniv,et al.  Towards using prosody to scaffold lexical meaning in robots , 2011, 2011 IEEE International Conference on Development and Learning (ICDL).