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IMPLEMENTING PERCEPTUAL SEMANTICS IN TYPE THEORY WITH RECORDS (TTR)

Abstract
Type Theory with Records (TTR) provides accounts of a wide range of semantic and linguistic phenomena in a single framework. This work proposes a TTR model of perception and language. Utilizing PyTTR, a Python implementation of TTR, the model is then implemented as an executable script. Over pure Python programming, TTR provides a transparent formal specification. The implementation is evaluated in a basic visual question answering (VQA) use case scenario. The results show that an implementation of a TTR model can account for multi-modal knowledge representation and work in a VQA setting.
Degree
Student essay
URI
http://hdl.handle.net/2077/62521
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  • Masteruppsatser / Master in Language Technology
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Master`s thesis (1.580Mb)
Date
2019-11-18
Author
Matsson, Arild
Keywords
visual question answering
artificial intelligence
type theory
image recognition
perceptual semantics
spatial relations
Language
eng
Metadata
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