Perceptual and objective detection of discontinuities in concatenative speech synthesis

Concatenative speech synthesis systems attempt to minimize audible signal discontinuities between two successive concatenated units. An objective distance measure which is able to predict audible discontinuities is therefore very important, particularly in unit selection synthesis, for which units are selected from among a large inventory at run time. In this paper, we describe a perceptual test to measure the detection rate of concatenation discontinuity by humans, and then we evaluate 13 different objective distance measures based on their ability to predict the human results. Criteria used to classify these distances include the detection rate, the Bhattacharyya measure of separability of two distributions, and receiver operating characteristic (ROC) curves. Results show that the Kullback-Leibler distance on power spectra has the higher detection rate followed by the Euclidean distance on Mel-frequency cepstral coefficients (MFCC)