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UT Austin statisticians develop new way to model how the brain learns language A cross-disciplinary team including University of Texas at Austin statisticians Giorgio Paulon and Abhra Sarkar have received the Mitchell Prize, a top prize in the field, for their study modeling what happens in the brains of nonnative English speakers learning another language s tonal differences. In Mandarin Chinese, for example, there are four ways to pronounce ma, and each one has a totally different meaning. Say it with a certain tone and it means mother. But beware say it slightly differently and it means horse. These tonal differences are rife in Mandarin but nonexistent in languages such as English. For some nonnative speakers, tonal differences make Mandarin especially difficult to master. They also make it an ideal case study for understanding how the human brain rewires itself to learn new languages which is what Sarkar, Paulon and their colleagues set out to discover.

United statesBharath chandrasekaranAbhra sarkarFernando llanosEmily hendersonGiorgio paulonDepartment of statisticsDepartment of linguisticsAmerican statistical associationMitchell prize founder committeeUt austin department of statisticsUniversity of texas at austinInternational society for bayesian analysisUniversity of pittsburghData sciencesMitchell prize