An efficient state detection of a person by fusion of acoustic and alcoholic features using various classification algorithms-Reference-Cited by-同舟云学术

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An efficient state detection of a person by fusion of acoustic and alcoholic features using various classification algorithms

Published:2020-06-30 Issue:3 Volume:23 Page:625-632
ISSN:1381-2416
Container-title:International Journal of Speech Technology
language:en
Short-container-title:Int J Speech Technol

Author:

Shenoi V. Viswanath^ORCID,Kuchibhotla Swarna,Kotturu Prasuna

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Link

http://link.springer.com/content/pdf/10.1007/s10772-020-09726-7.pdf

Reference36 articles.

1. Anne, K. R., Kuchibhotla, S., & Vankayalapati, H. D. (2015). Acoustic modeling for emotion recognition. New York: Springer.

2. Bernstein, J. P., Mendez, B. J., Sun, P., Liu, Y., & Shang, Y. (2017). Using deep learning for alcohol consumption recognition. In 2017 14th IEEE annual consumer communications & networking conference (CCNC) (pp. 1020–1021).

3. Busso, C., Deng, Z., Yildirim, S., Bulut, M., Lee, C. M., Kazemzadeh, A., et al. (2004). Analysis of emotion recognition using facial expressions, speech and multimodal information. In Proceedings of the 6th international conference on multimodal interfaces (pp. 205–211).

4. Cernak, M., Asaei, A., & Hyafil, A. (2018). Cognitive speech coding: Examining the impact of cognitive speech processing on speech compression. IEEE Signal Processing Magazine, 35(3), 97–109.

5. Davletcharova, A., Sugathan, S., Abraham, B., & James, A. P. (2015). Detection and analysis of emotion from speech signals. Procedia Computer Science, 58, 91–96.

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