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T1  - Assessing text readability and quality with language models 
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UR  - URN:NBN:fi:hulib-202003191584; http://hdl.handle.net/10138/313475 
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A1  - Liu, Yang 
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PB  - Helsingin yliopisto 
Y1  - 2020 
LA  - eng 
AB  - Automatic readability assessment is considered as a challenging task in NLP due to its high degree of subjectivity. The majority prior work in assessing readability has focused on identifying the level of education necessary for comprehension without the consideration of text quality, i.e., how naturally the text flows from the perspective of a native speaker. Therefore, in this thesis, we aim to use language models, trained on well-written prose, to measure not only text readability in terms of... 
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KW  - none; Algoritmit; Algorithms; Algoritmer; Tietojenkäsittelytieteen maisteriohjelma; Master's Programme in Computer Science; Magisterprogrammet i datavetenskap 
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