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.