Inferring rules for finding syllables in Spanish

Abstract

This paper presents how machine learning can be used to automatically obtain rules to divide words in Spanish into syllables. Machine learning is used in this case not only as a classifier to decide when a rule is used but to generate meaningful rules which then can be used to syllabify new words. Syllabification is an important task in speech recognition and synthesis since every syllable represents the sound in a single effort of articulation. Experiments were carried out using an Inductive Logic Programming (ILP) tool. The experiments were made on different sets of words to ascertain the importance of the number of examples in obtaining useful rules. The results show that it is possible to automatically obtain rules for syllabifying. © Springer-Verlag Berlin Heidelberg 2005.