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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)
In predicting subjective quality of speech signal degraded by telecommunication networks, conventional objective models require a reference source speech signal, which is applied as an input to the network, as well as the degraded speech. Non-intrusive estimation of speech quality is a challenging problem in that only the degraded speech signal is(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 investigate a new paradigm of objective speech quality estimation. The proposed nonintrusive method utilizes only processed speech signal, whereas conventional objective models require source speech applied as an input to the system under test, as well as the processed speech. The proposed method is based on the temporal envelope(More)