Syllable onset detection applied to the portuguese language

Recent developments have suggested that the use of syllables as the basic unit in a speech recognition system could be very usefull. Since syllable boundaries are more precise and well de ned than phoneme ones there is a large scope for their application on the continuous speech recognition process. In this work we developed di erent methods of syllable segmentation in continuous speech. These methods are based on perceptually oriented feature extraction techniques. These features were post-processed through simple threshold mechanisms or by an arti cial neural network based classi er in order to estimate the syllable boundaries. These systems were trained and evaluated using a Portuguese database with continuous speech. The results show that large context input windows (260ms) are the most appropriate, achieving results of 93% detection of onsets with insertion rates of only 15%.