The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Fuzzy Logic Applied for Pronunciation Assessment
Abstract
Pronunciation teaching is an important stage in language learning activities. This article tackles the pronunciation scoring problem where research has demonstrated relatively low human-human and low human-machine agreement rates, which makes teachers skeptical about their relevance. To overcome these limitations, a fuzzy combination of two machines scores is suggested. The experiments were carried in the context of Algerian pupils learning to read Arabic. Although the native language of Algerian pupils is a dialect of Arabic, Modern Standard Arabic remains difficult for them with difficult sounds to master and letters close in their pronunciation. The article presents a fuzzy evaluation system including both oral reading fluency, and intelligibility. The fuzzy system has shown that despite the disparities between human ratings, its scores correspond at least to one of their ratings and most of the time its ratings are in favor of learners. Therefore, fuzzy logic, more favorable than thresholding systems, encourages learners to pursue their training.
Related Content
|
Assim S. Alrajhi.
© 2024.
16 pages.
|
|
Baoxin Feng, Lee-Luan Ng.
© 2024.
17 pages.
|
|
Assim S. Alrajhi.
© 2023.
15 pages.
|
|
Amily Guenier.
© 2023.
15 pages.
|
|
Jinghe Han, Qiaoyun Liu, Ruiyan Sun.
© 2023.
16 pages.
|
|
Jakub Helvich, Lukas Novak, Petr Mikoska, Stepan Hubalovsky.
© 2023.
21 pages.
|
|
Tingting Wang, Haixia He.
© 2023.
17 pages.
|
|
|