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» Regularized Linear Prediction of Speech
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CORR
2011
Springer
205views Education» more  CORR 2011»
13 years 16 days ago
Parallel Coordinate Descent for L1-Regularized Loss Minimization
We propose Shotgun, a parallel coordinate descent algorithm for minimizing L1regularized losses. Though coordinate descent seems inherently sequential, we prove convergence bounds...
Joseph K. Bradley, Aapo Kyrola, Danny Bickson, Car...
IPMI
2011
Springer
13 years 6 days ago
Generalized Sparse Regularization with Application to fMRI Brain Decoding
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Bernard Ng, Rafeef Abugharbieh
ICASSP
2008
IEEE
14 years 3 months ago
Exploiting temporal change of pitch in formant estimation
This paper considers the problem of obtaining an accurate spectral representation of speech formant structure when the voicing source exhibits a high fundamental frequency. Our wo...
Tao T. Wang, Thomas F. Quatieri
ICASSP
2011
IEEE
13 years 15 days ago
Study of robustness of zero frequency resonator method for extraction of fundamental frequency
The objective of this work is to develop and study the robustness of the zero frequency resonator (ZFR) based method for extraction of the fundamental frequency (F0) of speech sig...
Bayya Yegnanarayana, S. R. Mahadeva Prasanna, S. G...
ISCAS
2003
IEEE
124views Hardware» more  ISCAS 2003»
14 years 2 months ago
Improving the filter bank of a classic speech feature extraction algorithm
The most popular speech feature extractor used in automatic speech recognition (ASR) systems today is the mel frequency cepstral coefficient (mfcc) algorithm. Introduced in 1980,...
Mark D. Skowronski, John G. Harris