Title
Efficient Implementation Of Statistical Model-Based Voice Activity Detection Using Taylor Series Approximation
Abstract
In this letter, we propose a simple but effective technique that improves statistical model-based voice activity detection (VAD) by both reducing computational complexity and increasing detection accuracy. The improvements are made by applying Taylor series approximations to the exponential and logarithmic functions in the VAD algorithm based on an in-depth analysis of the algorithm. Experiments performed on a smart-phone as well as on a desktop computer with various background noises confirm the effectiveness of the proposed technique.
Year
DOI
Venue
2014
10.1587/transfun.E97.A.865
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
Keywords
Field
DocType
voice activity detection, Taylor series approximation, embedded systems
Exponential function,Computer science,Voice activity detection,Algorithm,Theoretical computer science,Speech recognition,Statistical model,Logarithm,Computational complexity theory,Taylor series
Journal
Volume
Issue
ISSN
E97A
3
0916-8508
Citations 
PageRank 
References 
2
0.36
4
Authors
4
Name
Order
Citations
PageRank
Chungsoo Lim1394.35
Soojeong Lee2515.93
Jae-Hun Choi3295.57
joonhyuk413626.87