Annika Lea Heuser
MIT EECS | CS+HASS Undergraduate Research and Innovation Scholar
Modeling German Language Acquisition
2019–2020
EECS
- Natural Language and Speech Processing
Robert C. Berwick
Suzanne Flynn
In order to understand and replicate human intelligence, we must better understand the cognitive computation underpinning the uniquely human skill of language. Here the operation Merge seems central. It builds hierarchical trees out of two syntactic elements. Without Merge, we would not be able to build complex descriptions of the world, which we then use for internal thought or external communication. The goal of this project is to build a true-to-theory computational model of Merge, in order to learn more about this critical operation. The programmed model will use its Merge function in exactly the same way to return a hierarchical tree for English or German sentences that it is given.
“I am participating in SuperUROP because I realize that my research will not make a difference unless I can clearly communicate about it. I will also gain valuable insight about the research process from playing a large role in the design of my project. I look forward to learning about English and German in a completely different way and to enhancing the programming skills that I have gained from my classes and internships.”