dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Marien, Hans | |
dc.contributor.author | Gramkow, Fleur | |
dc.date.accessioned | 2023-08-29T00:00:51Z | |
dc.date.available | 2023-08-29T00:00:51Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/44798 | |
dc.description.abstract | Low-literacy poses a significant problem in the Netherlands, with an anticipated increase to
3.5 million low-literate individuals in 2024. Low-literacy individuals encounter daily
challenges in areas such as healthcare, education and work. Numerous low-literate
individuals remain unidentified because of intimidating testing methods and provided help by
others. Incomplete insights in the actual problem makes it challenging to provide solutions
for low-literate individuals. Speech-to-text software can provide solutions to investigate the
actual literate levels of individuals by examining word recognition based on audio signals.
This provides a less intimidating research method since it examined how well the software
converts speech to text, rather than the performance of the low-literate individual. In current
research, word recognition is investigated by simulating speech-to-text software, while
examining the factors contributing to word recognition; age of acquisition and frequency.
Current study focuses on the question to what extent the performance on a visual word
recognition task is dependent on age of acquisition and frequency of used words. Results
supported the influence of age of acquisition and frequency of used words on the reaction
time and error rates on a visual word recognition task. Furthermore, the effect of age of
acquisition and frequency of used words is not significantly greater when having to reject the
words in the visual word recognition task. Current study offers a more thorough
understanding of word processing and its application in speech-to-text software for
low-literate individuals. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | Low-literacy is a substantial problem in the Netherlands, and the actual levels of low-literate individuals seem to be unknown. Speech-to-text software can provide solutions to investigate the actual literate levels of individuals by examining word recognition based on audio signals. In current research, word recognition is investigated by simulating speech-to-text software, while examining the factors contributing to word recognition; age of acquisition and frequency. | |
dc.title | The influence of age of acquisition and frequency of used words on a visual word recognition task. | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | age of acquisition; frequency; low-literacy; speech-to-text software; visual word
recognition task | |
dc.subject.courseuu | Social, Health and Organisational Psychology | |
dc.thesis.id | 22851 | |