It sounds like Greek to me
Performance of phonetic representations for language identification
D.J. IJpma (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Tom Julian Viering – Mentor (TU Delft - Computer Science & Engineering-Teaching Team)
M Loog – Coach (TU Delft - Pattern Recognition and Bioinformatics)
Stavros Makrodimitris – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
Arman Naseri Jahfari – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
Catherine Oertel – Coach (TU Delft - Interactive Intelligence)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
This paper compares the performance of two phonetic notations, IPA and ASJPcode, with the alphabetical notation for word-level language identification. Two machine learning models, a Multilayer Percerptron and a Logistic Regression model, are used to classify words using each of the three notations. With both models the IPA notation outperforms the other two notations.