Daniel P. Jarrett

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The problem of acoustic source localization is important in many acoustic signal processing applications, such as distant speech acquisition and automated camera steering. In noisy and reverberant environments, the source localization problem becomes challenging and many existing algorithms deteriorate. Three-dimensional source localization presents(More)
A method is proposed for simulating the sound pressure signals on a spherical microphone array in a reverberant enclosure. The method employs spherical harmonic decomposition and takes into account scattering from a solid sphere. An analysis shows that the error in the decomposition can be made arbitrarily small given a sufficient number of spherical(More)
—In this letter, we derive an expression for the expected incoherent noise reduction factor of a spherical harmonic domain (SHD) tradeoff beamformer. The tradeoff beamformer attempts to reduce noise while minimizing speech distortion, and includes the minimum variance distortionless response (MVDR) and multi-channel Wiener filters as special cases. For the(More)
In noise reduction, a common approach is to use a microphone array with a beamformer that combines the individual microphone signals to extract a desired speech signal. The beamformer weights usually depend on the statistics of the noise and desired speech signals, which cannot be directly observed and must be estimated. Estimators based on the speech(More)
Most beamformers used for noise reduction rely on the accurate estimation of the second-order statistics of the noise, and in some cases, of the desired signal. Speech presence probability (SPP) based statistics estimators seek to update the estimates only when speech is ab-sent/present, however, when used with a fixed a priori SPP, they cannot distinguish(More)
In speech communication systems the received microphone signals are commonly degraded by reverberation and ambient noise that can decrease the fidelity and intelligibility of a desired speaker. Reverberation can be modeled as non-stationary diffuse sound which is not directly observable. In this work, we derive a multichannel Wiener filter in the spherical(More)
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