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Non-intrusive estimation of speech quality is a challenging problem in that the estimation has to be performed without the original reference speech signals. This paper presents a new American national standard (ANS) for nonintrusive estimation of narrowband speech quality. The proposed auditory non-intrusive quality estimation plus (ANIQUE ) model is a(More)
The Ensemble Interval Histogram (EIH) is an auditory model which can be used as a robust \front-end" for speech recognition systems. The utilization of multiple level-crossing detectors in the EIH provides frequency and intensity information, which may be useful for speech processing. Proper determination of the number of levels and the level values is very(More)
In order to estimate the quality of degraded speech processed by communication networks, conventional objective speech quality assessment methods require the source speech signal, which has been applied to the networks, as well as the processed speech. The paper presents a new paradigm in objective speech quality assessment. In contrast to previous(More)
An intelligent judge neural network (IJNN) is developed to make decisions out of contradictory arguments, which may come from different classifiers with different characteristics and/or input features. For speech recognition applications a multi-layer perceptron classifies the word as a spectro-temporal pattern, while a neural prediction model or(More)
In this paper, we propose a novel model for estimating the quality of speech without the reference speech information. The proposed auditory non-intrusive quality estimation plus (ANIQUE+) model is a perceptual model simulating the functional role of human auditory system, and employs improved modeling of quality estimation by statistical learning methods.(More)