
Abstract In this study, we have examined the acoustic characteristics of whispered speech and addressed some of the issues involved in recognition of whispered speech used for communication over a mobile phone in a noisy environment. The acoustic analysis shows that there is an upward shift of formant frequencies of vowels as observed in the whispered speech data compared to the normal speech data. Voiced consonants in the whispered speech have lower energy at low frequencies up to 1.5 kHz and their spectral flatness is greater compared to the normal speech. In experiments on whispered speech recognition, results of our studies on adaptation of the whispered speech models have shown that adaptation using a small amount of whispered speech data from a target speaker can be effectively used for recognition of the whispered speech. In a noisy environment, the recognition accuracy decreases significantly for the whispered speech compared to the normal speaking of the same speech. A method to increase the SNR by covering the mouth with a hand has been shown to give a higher recognition accuracy for the whispered speech frequently encountered for private communication in a noisy environment.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 134 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
