Acoustical and Lexical/syntactic Features to Predict Prominence

In this study acoustical as well as lexical/syntactic correlates of prominence are analyzed and discussed. Prominence is defined at the word level and is based on listener judgments. Spoken sentences from many different speakers, taken from the Dutch Polyphone corpus of telephone speech, are analyzed. A selection of useful acoustical input features is chosen for classification of word prominence, by means of Feed Forward Nets. For an independent test set of 1,000 sentences about 79% of the words are correctly classified as prominent or not. We also developed an algorithm, based on text input, using linguistic/syntactical features derived from text only, to predict prominence. The prediction agrees with the perceived prominence in 81% of the cases for the independent test set. The results of this project show that certain acoustical and linguistic correlates of prominence can be extracted automatically and can be used to accurately predict prominence with a consistency similar to the pominence assignment by naive listeners.