Paper
15 October 2021 An acoustic study on the whispery voice
Suisui Xu, Wen Liu
Author Affiliations +
Proceedings Volume 11933, 2021 International Conference on Neural Networks, Information and Communication Engineering; 119331H (2021) https://doi.org/10.1117/12.2615299
Event: 2021 International Conference on Neural Networks, Information and Communication Engineering, 2021, Qingdao, China
Abstract
Whispery voice is a type of voice quality in which the vocal folds do not vibrate and the airflow through the resonating cavity is modulated. Previous studies have shown that there is no fundamental frequency but has formant envelope in whispery voice. This is why the listener can recognize the voice quality. In this study, acoustic and spectral measures are extracted to investigate the formant pattern and voice quality of whispery voice. The results show that the differences in harmonic amplitudes (H4-H2K, H2K-H5K) are more effective in distinguishing whispered speech from modal voice than the differences in harmonic amplitudes at low frequencies (H1-H2, H2-H4). In addition, the values of Harmonic-to-Noise Ratio (HNR) and Cepstral Peak Prominence (CPP) of whispered voice were significantly lower than that of modal phonation, and the acoustic energy of whispery voice was also significantly reduced. As to formant frequency, the lower formant frequency of whispered vowels became higher compared to those of modal phonation. These findings can not only reveal the acoustic characteristics of whispery voice, but also provide theoretical foundation for whisper automatic recognition.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Suisui Xu and Wen Liu "An acoustic study on the whispery voice", Proc. SPIE 11933, 2021 International Conference on Neural Networks, Information and Communication Engineering, 119331H (15 October 2021); https://doi.org/10.1117/12.2615299
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KEYWORDS
Acoustics

Modulation

Lithium

Acoustic coupling

Cartilage

Data analysis

Excel

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