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Department of Computational Linguistics

Transition probabilities and word recognition

Supervisor: Dr. Catalina Torres


Transition probabilities (TPs) of segments or syllables are considered helpful in language processing. Experimental procedures using artificial languages have confirmed that listeners exploit these probabilities and can learn and then recognise new words. This project aims at investigating the TPs in two natural human languages spoken by a bilingual population. The goal of the thesis will be to explore and provide metrics of TPs for two languages that differ in their linguistic structure but also their status as well-resourced vs. under-resourced. This will inform the predictability of a given set of words in the two languages.


  • Python or R or Matlab