Comparative study of Automatic Phone Segmentation methods for TTS
Jordi Adell Segura, Antonio Bonafonte, Jon Ander Gómez, María José Castro · 2006
We present two novel approaches to phonetic speech segmentation. One is based on acoustical clustering plus dynamic time warping and the other is based on a boundary specific correction by means of a decision tree. The use of objective or perceptual evaluations is discussed. The novel approaches clearly outperform the objective results of the baseline system based on HMM. They get results similar to agreement between manual segmentations. We show how phonetic features can be successfully used for boundary detection together with HMMs. Finally, the need for perceptual tests in order to evaluate segmentation systems is pointed out.