Modeling liaison in French by using decision trees

French is known to be a language with major pronunciation irregularities at word endings with consonants. Particularly, the well-known phonetic phenomenon called Liaison is one of the major issues for French phonetizers. Rule-based methods have been used to solve these issues. Yet, the current models still produce a great number of pronunciation errors to be used in 2nd language learning applications. In addition, the number of rules tends to be large and their interaction complex, making maintenance a problem. In order to try to alleviate such problems, we propose here an approach that, starting from a database (compiled from cases documented in the literature), allows us to build C4.5 decision trees and subsequently, automate the generation of the required rules. A prototype based on our approach has been tested against six other state-of-theart phonetizers. The comparison shows the prototype system is better than most of them, being equivalent to the second-rank system.