Jesus college choir binaural recording2/29/2024 The ability to replicate a plane wave represents an essential element of spatial sound field reproduction. The regularization parameter can be further increased to improve performance depending on the control effort constraints, expected magnitude of errors, and desired sound field properties of the system. A frequency-dependent minimum regularization parameter is determined based on the conditioning of the matrix inverse. Judicious selection of the regularization parameter is shown to be a primary concern for sound zone system designers - the acoustic contrast can be increased by up to 50dB with proper regularization in the presence of errors. Results are obtained for speed of sound variations and loudspeaker positioning errors with respect to the source weights calculated. Simulations show that regularization has a significant effect on the sound zone performance, both under ideal anechoic conditions and when systematic errors are introduced between calculation of the source weights and their application to the system. Regularization governs the control effort required to drive the loudspeaker array, via a constraint in each optimization cost function. In this study, the effects of regularization are analyzed for three representative sound zoning methods. Recent attention to the problem of controlling multiple loudspeakers to create sound zones has been directed towards practical issues arising from system robustness concerns. I have over 200 journal, patent, conference and book publications (Google h-index=30) and served as associate editor for Computer Speech and Language (Elsevier), and as reviewer for the Journal of the Acoustical Society of America, IEEE/ACM Transactions on Audio, Speech and Language Processing, IEEE Signal Processing Letters, InterSpeech and ICASSP. I joined CVSSP in 2002 after a UK postdoctoral fellowship at University of Birmingham, with a PhD in Electronics and Computer Science from University of Southampton (2000) and MA from Cambridge University Engineering Department (1997). Currently sound localisation, audio-visual talker tracking, object-based media production and responsible AI are my foci. I have contributed to various sound-related technologies: active noise control for aircraft, speech aero-acoustics, source separation and articulatory models for automatic speech recognition, audio-visual emotion classification and visual speech synthesis, including new techniques for spatial audio and personal sound. I am interested in what machines can do with acoustical signals, including speech, music and the everyday sounds that surround us. Sound carries a multiplicity of information about what is going on all around you: from who, what, where and when to the meaning of a story being told.
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