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This paper presents a new approach to an auditory model for robust speech recognition in noisy environments. The proposed model consists of cochlear bandpass lters and nonlinear operations in which frequency information of the signal is obtained by zero-crossing intervals. Intensity information is also incorporated by a peak detector and a compressive(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)
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)