The conversion method from Non-Audible Murmur (NAM) to ordinary speech based on the statistical voice conversion (NAM-toSpeech) has been proposed towards realization of “silent speech telephone.” Although NAM-to-Speech converts NAM to intelligible voices with similar quality to speech, there is still a large problem, i.e., difficulties of the F0 estimation from unvoiced speech. In order to avoi...

background: previous studies have shown that interaural-time-difference (itd) training can improve localization ability. surprisingly little is, however, known about localization training vis-à-vis speech perception in noise based on interaural time difference in the envelope (itd env). we sought to investigate the reliability of an itd env-based training program in speech-in-noise perception a...

speech emotion can add more information to speech in comparison to available textual information. however, it will also lead to some problems in speech recognition process. in a previous study, we depicted the substantial changes of speech parameters caused by speech emotion. therefore, in order to improve emotional speech recognition rate, in a first step, the effects of emotion on speech par...

Speech recognition, the problem of performance degradation is the difference between the model training and recognition environments. Silence features normalized using the method as a way to reduce the inconsistency of such an environment. Silence features normalized way of existing in the low signal-to-noise ratio. Increase the energy level of the silence interval for speech and non-speech cla...

One of the basic problems in speech engineering is phoneme segmentation, that is, to divide a speech stream into a string of phonemes. Automatic Speech Recognition (ASR) models often require reliable phoneme segmentation in the initial training phase, and Text-to-Speech (TTS) systems need a large speech database with correct phoneme segmentation information for improving the performance. Human ...