Restoring the missing features of the corrupted speech using linear interpolation methods-Reference-Cited by-同舟云学术

Restoring the missing features of the corrupted speech using linear interpolation methods

Published:2017 Issue: Volume: Page:
ISSN:0094-243X
Container-title:AIP Conference Proceedings
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Author:

Rassem Taha H.,Makbol Nasrin M.,Hasan Ali Muttaleb,Zaki Siti Syazni Mohd,Girija P. N.

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Author(s)

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5005452

Reference11 articles.

1. M. L. Seltzer, “Automatic detection of corrupt spectrographic features for robust speech recognition.” PhD thesis, Carnegie Mellon University, 2000.

2. B. R. Ramakrishnan, “Reconstruction of incomplete spectrograms for robust speech recognition.” PhD thesis, Carnegie Mellon University, 2000.

3. Y. Wang, J. F. Gemmeke and K. Demuynck. Missing data solutions for robust speech recognition. in Essential Speech and Language Technology for Dutch (Springer, 2013), pp. 289–304.

4. Robust automatic speech recognition with missing and unreliable acoustic data

5. Reconstruction of missing features for robust speech recognition

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