Syllabification with Frequent Sequence Patterns - A Language Independent Approach
Adrian Bona, Camelia Lemnaru, Rodica Potolea · 2016
In this paper we show how words represented as sequences of syllables can provide valuable patterns for achieving language independent syllabification. We present a novel approach for word syllabification, based on frequent pattern mining, but also a more general framework for syllabification. Preliminary evaluations on Romanian and English words indicated a word level accuracy around 77% for Romanian words and around 70% for English words. However, we believe the method can be refined in order to improve performance.