Modeling segmental duration with multivariate adaptive regression splines

Abstract

The application of "Multivariate Adaptive Regression Splines" (MARS) to the problem of modeling duration of a set of segments used in a text-to-speech system for German is presented. MARS is a technique to estimate general functions of high-dimensional arguments given sparse data. It automatically selects the parameters and the structure of the model based on data available. The result is a model with a correlation coefficient between observed and predicted durations of a test set of 0:90. Besides highly accurate predicting durations, a MARS model also allows interpretation of its structure, demonstrated in this study by analyses of factor importance and interactions of the MARS model.