Automatic speech signal segmentation based on the innovation adaptive filter
Ryszard Makowski, Robert Hossa (2014)
International Journal of Applied Mathematics and Computer Science
Similarity:
Ryszard Makowski, Robert Hossa (2014)
International Journal of Applied Mathematics and Computer Science
Similarity:
Ryszard Makowski, Robert Hossa (2014)
International Journal of Applied Mathematics and Computer Science
Similarity:
Ewa Świercz (2010)
International Journal of Applied Mathematics and Computer Science
Similarity:
A new supervised classification algorithm of a heavily distorted pattern (shape) obtained from noisy observations of nonstationary signals is proposed in the paper. Based on the Gabor transform of 1-D non-stationary signals, 2-D shapes of signals are formulated and the classification formula is developed using the pattern matching idea, which is the simplest case of a pattern recognition task. In the pattern matching problem, where a set of known patterns creates predefined classes,...
Miroslav L. Dukić, Zoran S. Dobrosavljević (1997)
Kybernetika
Similarity:
Chawla, M.P.S. (2007)
Computational & Mathematical Methods in Medicine
Similarity:
Petr Tichavský, Zbyněk Koldovský (2011)
Kybernetika
Similarity:
This paper presents a survey of recent successful algorithms for blind separation of determined instantaneous linear mixtures of independent sources such as natural speech or biomedical signals. These algorithms rely either on non-Gaussianity, nonstationarity, spectral diversity, or on a combination of them. Performance of the algorithms will be demonstrated on separation of a linear instantaneous mixture of audio signals (music, speech) and on artifact removal in electroencephalogram...
Ma, Zichen, Fokoue, Ernest (2014)
Serdica Journal of Computing
Similarity:
It is well established that accent recognition can be as accurate as up to 95% when the signals are noise-free, using feature extraction techniques such as mel-frequency cepstral coefficients and binary classifiers such as discriminant analysis, support vector machine and k-nearest neighbors. In this paper, we demonstrate that the predictive performance can be reduced by as much as 15% when the signals are noisy. Specifically, in this paper we perturb the signals with different levels...
Majumdar, Kaushik, Myers, Mark H. (2006)
Computational & Mathematical Methods in Medicine
Similarity:
Bessios, Anthony G., Caimi, Frank M. (1996)
Mathematical Problems in Engineering
Similarity: