Tsutomu Sugawara

Effects of the Phonological Contents on Perceptual Speaker Identification

It is known that the accuracy of perceptual speaker identification is dependent on the stimulus contents presented to the subjects. Two experiments were conducted in order to find out the effective sounds and to investigate the effects of the syllable structures on familiar speaker identification. The results showed that the nasal sounds were effective for identifying the speakers both in onset and coda positions, and coronal sounds were more effective than labial counterparts. The onset consonants were found to be important, and the identification accuracy was degraded in onsetless structures.

Phoneme dependency of accuracy rates in familiar and unknown speaker identification

For perceptual speaker identification, the identification accuracy depends on the speech contents presented to subjects. Our previous studies have shown that stimuli containing nasals are effective for identifying familiar speakers [Amino et al., Acoust. Sci. Tech. 27(4) (2006)]. We have also presented the possibility that the interspeaker spectral distances reflect perceptual speaker similarities. In the present study, we conducted an experiment in which four unknown speakers were identified by 15 subjects. The stimuli were identical to those used in the previous study, in which ten speakers were identified by familiar listeners, although the speakers were fewer this time. Nine consonants in the CV structure were used as stimuli. The consonants were /d/, /t/, /z/, /s/, /r/, /j/, /m/, /n/, and /nj/; the vowel was restricted to /a/ for all CV syllables to simplify the experiment. The results showed that the nasals /n/ and /nj/ obtained higher scores. Tendencies in the differences among consonants were on the same order as those of the previous experiment, but the average scores were lower than those for familiar listeners. [Work supported by Grant‐in‐Aid for JSPS Fellows 17‐6901.]

Building an English speech synthetic voice using a voice transformation model from a Japanese male voice

This work reports development of an English speech synthetic voice using a voice transformation model for a Japanese amyotrophic lateral sclerosis patient as part of a project of developing a bilingual communication aid for this patient. The patient, who had a tracheotomy 3 years ago and had difficulty in speaking, wishes to speak in his own voice in his native language and in English. A Japanese speech synthesis system was developed using atr chatr 6 years ago and the authors have worked in developing a diphone‐based synthesis using festival speech synthesis system and festvox by having the patient read the diphone list. However, it was not an easy task for the patient to phonate and, moreover, to pronounce words in a foreign language. We therefore used a voice transformation model in festival to develop the patient’s English speech synthetic voice which enables text‐to‐speech synthesis. We trained using 30 sentences read by the patient and those synthesized with an existing festival diphone voice create...