Paul Kendrick

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This paper compares two methods for extracting room acoustic parameters from reverberated speech and music. An approach which uses statistical machine learning, previously developed for speech, is extended to work with music. For speech, reverberation time estimations are within a perceptual difference limen of the true value. For music, virtually all early(More)
This letter proposes a new variable tap-length least-mean-square (LMS) algorithm for applications in which the unknown filter impulse response sequence has an exponential decay envelope. The algorithm is designed to minimize the mean-square deviation (MSD) between the optimal and adaptive filter weight vectors at each iteration. Simulation results show the(More)
A new variable step-size least-mean-square (VSSLMS) algorithm is presented in this paper for applications in which the desired response contains nonstationary noise with high variance. The step size of the proposed VSSLMS algorithm is controlled by the normalized square Euclidean norm of the averaged gradient vector, and is henceforth referred to as the(More)
A new framework is proposed in this paper to solve the reverberation time (RT) estimation problem in occupied rooms. In this framework, blind source separation (BSS) is combined with an adaptive noise canceller (ANC) to remove the noise from the passively received reverberant speech signal. A polyfit preprocessing step is then used to extract the free decay(More)
A new method, employing machine learning techniques and a modified low frequency envelope spectrum estimator, for estimating important room acoustic parameters including reverberation time (RT) and early decay time (EDT) from received music signals has been developed. It overcomes drawbacks found in applying music signals directly to the envelope spectrum(More)
Wind can induce noise on microphones, causing problems for users of hearing aids and for those making recordings outdoors. Perceptual tests in the laboratory and via the Internet were carried out to understand what features of wind noise are important to the perceived audio quality of speech recordings. The average A-weighted sound pressure level of the(More)