A study of high quality speech synthesis based on the analysis of the randomness in speech signals

Randomness observed in human speech signals is considered to be a key factor in the naturalness of human speech. This research project has investigated the characteristics of several kinds of randomness observed in human speech signals phonated by normal speakers. Based on the results of the analysis, some advanced techniques for artificially reproducing such randomness were developed with the aim of enhancing the voice quality of synthesized speech. The types of randomness particularly investigated in this project were: (1) amplitude fluctuation, (2) period fluctuation, (3) waveform fluctuation, (4) random fractalness of the source signals obtained by linear predictive analysis, and (5) unvoiced characteristics, namely, aperiodicity observed in voiced consonants. Using their statistical characteristics, a simple model was made for these forms of randomness, and was evaluated how it could contribute to realize high quality speech synthesis systems based on the LPC (linear predictive coding) vocoder. Normal sustained vowels always contain a cyclic change of maximum peak amplitudes and pitch periods, even at those times when the values seem to be quite stable. This project investigated the statistical characteristics of the fluctuations that were particularly labeled amplitude fluctuation and period fluctuation, respectively. Since the frequency characteristics of these fluctuation sequences appeared to be roughly subject to a 1/f power law, the author reached the conclusion that amplitude and period fluctuation could be modeled as 1/f fluctuations for a preliminary model. Psychoacoustic experiments performed in this study indicated that the differences in the frequency characteristics of the amplitude and period fluctuation could potentially influence the voice quality of synthesized speech. Compared with 1/f (white noise), 1/f , and 1/f 3 fluctuation models, amplitude and period fluctuation modeled as 1/f fluctuations could produce voice quality which was more similar to that of human speech phonated by normal speakers. Normal sustained vowels also always contain a cyclic change of the waveform itself, even during their most steady parts. This project investigated the statistical characteristics of the waveform fluctuations extracted from the residual signals of the LPC vocoder. Since the frequency characteristics of the waveform fluctuations appeared to be subject to a 1/f power law, the author reached the conclusion that the waveform fluctuations could be modeled as 1/f fluctuations for a preliminary model. Psychoacoustic experiments performed in this study indicated that the differences in the frequency characteristics of waveform fluctuations could potentially influence the voice quality of synthesized speech. Compared with 1/f 0 (white noise), 1/f , and 1/f 3 fluctuation models, waveform fluctu-