Prediction of word prominence

Control of prosody is essential for the synthesis of natural sounding speech. Text-to-speech systems tend to accent too many words when taking into account only the distinction between open-class and closed-class words. In the prominence-based approach [1], the degree of accentuation of a syllable is described in terms of a gradual prominence parameter. This paper presents the calculation of the prominence level of words based on their word class, the classes of the surrounding words, and their position in a clause. Rules predicting word prominence are derived from statistical analysis of a prosodic database. The hand-crafted rules are compared with the results of several machine learning algorithms on the same material. Furthermore, a perceptual test and an analysis of the resulting speech signals are carried out.