Investigating the Recognition of Non-articulatory Sounds by Using Statistical Tests and Support Vector Machine-Reference-Cited by-同舟云学术

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Investigating the Recognition of Non-articulatory Sounds by Using Statistical Tests and Support Vector Machine

Published:2018 Issue: Volume: Page:639-649
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Souza Francisco Carlos M.,Souza Alinne C. Corrêa,Nakamura Gilberto M.,Soares M. D.,Mandrá Patrícia Pupin,Macedo Alessandra A.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-77028-4_82

Reference17 articles.

1. B. Dodd, L. Thompson, Speech disorder in children with down’s syndrome. J. Intellect. Disabil. Res. 4, 308–316 (2001)

2. A. Hennequin, A. Rochet-Capellan, M. Dohen, Auditory-visual perception of VCVs produced by people with down syndrome: preliminary results, in 17th Annual Conference of the International Speech Communication Association (Interspeech 2016), San Francisco, Sept. 2016

3. R.D. Kent, Nonspeech oral movements and oral motor disorders: a narrative review. Am. J. Speech Lang. Pathol. 24, 763–789 (2015)

4. H. Sakoe, S. Chiba, Dynamic programming algorithm optimization for spoken word recognition, in Readings in Speech Recognition, ed. by A. Waibel, K.-F. Lee (Morgan Kaufmann Publishers Inc., San Francisco, CA, 1990), pp. 159–165. Available: http://dl.acm.org/citation.cfm?id=108235.108244

5. A. Alatwi, S. So, K.K. Paliwal, Perceptually motivated linear prediction cepstral features for network speech recognition, in 10th International Conference on Signal Processing and Communication Systems, ICSPCS 2016, Surfers Paradise, Gold Coast, Australia, December 19–21, 2016 (2016), pp. 1–5

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