12th Annual Conference of the International Speech Communication Association

Florence, Italy
August 27-31. 2011

Neural Representations of Word Meanings

Tom M. Mitchell

E. Fredkin University; Machine Learning Department School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA

How does the human brain represent meanings of words and pictures in terms of neural activity? This talk will present our research addressing this question, by applying machine learning algorithms to fMRI and MEG brain image data. One line of our research involves training classifiers that identify which word a person is thinking about, based on their observed neural activity. A second line involves training computational models that predict the neural activity associated with arbitrary English words, including words for which we do not yet have brain image data. A third line of work involves examining neural activity at millisecond time resolution during the comprehension of words and phrases.


Professor Tom M. Mitchell is a professor in the E. Fredkin University and head of the Machine Learning Department at Carnegie Mellon University. His research interests lie in cognitive neuroscience, machine learning, natural language processing, and artificial intelligence. Mitchell is a member of the US National Academy of Engineering, a Fellow of the American Association for the Advancement of Science (AAAS), and Fellow and Past President of the Association for the Advancement of Artificial Intelligence (AAAI). Mitchell believes the field of machine learning will be the fastest growing branch of computer science during the 21st century.

Bibliographic reference.  Mitchell, Tom M. (2011): "Neural representations of word meanings", In INTERSPEECH-2011 (abstract).