Intonation modeling for Indian languages

In this paper we study neural network models to capture intonation patterns of speech in Indian languages. We examine the performance of neural networks and support vector machines (SVM) for this purpose. Modeling the intonation pattern is the task of predicting the sequence of fundamental frequency (f0) values for the sequence of syllables in the given text. Analysis is performed on broadcast news data in the languages Hindi, Telugu and Tamil, in order to predict the f0 of syllables in these languages using neural network and SVM models. The input to both the models consists of a set of phonological, positional and contextual features extracted from the text.