A
Andreas Spanias
Researcher at Arizona State University
Publications - 512
Citations - 8918
Andreas Spanias is an academic researcher from Arizona State University. The author has contributed to research in topics: Speech coding & Speech processing. The author has an hindex of 36, co-authored 490 publications receiving 7895 citations. Previous affiliations of Andreas Spanias include Arizona's Public Universities & Intel.
Papers
More filters
Journal Article
A new approach towards predictability of epileptic seizures: KLT dimension.
Rajeshkumar Venugopal,K. Narayanan,Awadhesh Prasad,Andreas Spanias,James Chris Sackellares,Leon D. Iasemidis +5 more
TL;DR: It is shown that 10 out of 15 seizures in one patient with temporal lobe epilepsy were predictable with an average predictability time of about 36 minutes, derived from the created KLT dimensionality profiles.
Book
MATLAB Software for the Code Excited Linear Prediction Algorithm: The Federal Standard-1016
TL;DR: This book describes several modules of the Code Excited Linear Prediction (CELP) algorithm using the Federal Standard-1016 CELP MATLAB(r) software to describe in detail several functions and parameter computations associated with analysis-by-synthesis linear prediction.
Journal ArticleDOI
Perceptual segmentation and component selection for sinusoidal representations of audio
Ted Painter,Andreas Spanias +1 more
TL;DR: Two fundamental enhancements in a hybrid audio signal model consisting of sinusoidal, transient, and noise (STN) components are presented, including a novel application of a perceptual metric for optimal time segmentation for the analysis of transients and a new methodology for ranking and selection of the most perceptually relevant sinusoids.
Proceedings ArticleDOI
On-line simulation modules for teaching speech and audio compression techniques
TL;DR: A collection of software educational tools for introducing speech and audio compression techniques to undergraduate and graduate students that enable online simulations of speech compression algorithms that are being used in digital cellular phones, Internet streaming applications, teleconferencing, and voice over Internet protocol (VoIP) applications are presented.
Journal ArticleDOI
Distributed SNR Estimation With Power Constrained Signaling Over Gaussian Multiple-Access Channels
TL;DR: It is shown that among the noise distributions considered, the estimators are asymptotically efficient only when the noise distribution is Gaussian, and Simulation results corroborate analytical results.