Reducing Speech Noise for Patients with Dysarthria in Noisy Environments
Author:
Affiliation:
1. School of Information and Communications, Gwangju Institute of Science and Technology (GIST)
2. Visual Display R&D Office, Samsung Electronics
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Link
https://www.jstage.jst.go.jp/article/transinf/E97.D/11/E97.D_2014EDP7130/_pdf
Reference22 articles.
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2. [2] M.S. Hawley, S.P. Cunningham, P.D. Green, P. Enderby, R. Palmer, S. Sehgal, and P. O'Neil, “A voice-input voice-output communication aid for people with severe speech impairment,” IEEE Trans. Neural Systems and Rehabilitation Engineering, vol.21, no.1, pp.23-31, Jan. 2013.
3. [3] M. Hasegawa-Johnson, J. Gunderson, A. Penman, and T. Huang, “HMM-based and SVM-based recognition of the speech of talkers with spastic dysarthria,” Proc. IEEE International Conf. Acoustics, Speech, and Signal Processing, pp.1060-1063, Toulouse, France, May 2006.
4. [4] H. Tolba and A.S. El Torgoman, “Towards the improvement of automatic recognition of dysarthric speech,” Proc. 2nd IEEE International Conf. Computer Science and Information Technology, pp.277-281, Beijing, China, Aug. 2009.
5. [5] R. Miyazaki, H. Saruwatari, T. Inoue, Y. Takahashi, K. Shikano, and K. Kondo, “Musical-noise-free speech enhancement based on optimized iterative spectral subtraction,” IEEE Trans. Audio Speech Language Process., vol.20, no.7, pp.2080-2094, Sept. 2012.
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