Simulating individual differences in language ability and genetic differences in FOXP2 using a neural network model of the SRT task

Posted on 1 Aug 2010 by Joe Toscano

Toscano, J. C., Mueller, K. L, McMurray, B., & Tomblin, J. B. (2010). In S. Ohlsson & R. Catrambone, Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 2230-2235). Austin, TX: Cognitive Science Society.

Abstract: Recent work has shown that individual differences in language development are related to differences in procedural learning, as measured by the serial reaction time (SRT) task... Read more →

Tagged with: computational modeling, connectionism, FOXP2, genetics, language processing, neural networks, procedural learning, serial reaction time task, simple recurrent networks, specific language impairment
Posted in Refereed conference proceedings

Using the distributional statistics of speech sounds for weighting and integrating acoustic cues

Posted on 1 Jul 2008 by Joe Toscano

Toscano, J. C. & McMurray, B. (2008). In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 433-438). Austin, TX: Cognitive Science Society.

Abstract: A great deal of behavioral evidence suggests that infants can use distributional statistics to learn speech sound categories. .. Read more →

Tagged with: computational modeling, cue integration, cue weighting, gaussian mixture models, speech development, speech perception, statistical learning, unsupervised learning
Posted in Refereed conference proceedings

Joe Toscano

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Simulating individual differences in language ability and genetic differences in FOXP2 using a neural network model of the SRT task

Using the distributional statistics of speech sounds for weighting and integrating acoustic cues