  ITU-R BS.1387 states a method for objective assessment of perceived audio
quality. This Recommendation, known also as PEAQ (Perceptual Evaluation of
Audio Quality) is based on a psychoacoustic model of the human ear and was
standardized by the International Telecommunications Union as an alternative to
subjective tests, which are expensive and time-consuming processes. PEAQ
combines various physiological and psycho-acoustical properties of the human
ear to give a measure of the quality difference between a reference audio and a
test audio. The reference audio signal could be considered as a distortion-free
source, whereas the test signal is a distorted version of the reference, which
may have audible artifacts because of compression. The algorithm computes the
Model Output Variables (MOVs) which are mapped to a single quality measure,
Objective Difference Grade (ODG), using a three-layer perceptron artificial
neural network. The ODG estimates the perceived distortion between both audio
signals. In this paper we propose a new metric of low computational complexity
called FQI (Fuzzy Quality Index) which is based on Fuzzy Logic reasoning and
has been incorporated into the existing PEAQ model to improve its overall
performance. Results show that the modified version slightly outperforms PEAQ.
