@article {18457,
	title = {Plane-Wave Decomposition of Acoustical Scenes Via Spherical and Cylindrical Microphone Arrays},
	journal = {IEEE Transactions on Audio, Speech, and Language Processing},
	volume = {18},
	year = {2010},
	month = {2010/01//},
	pages = {2 - 16},
	abstract = {Spherical and cylindrical microphone arrays offer a number of attractive properties such as direction-independent acoustic behavior and ability to reconstruct the sound field in the vicinity of the array. Beamforming and scene analysis for such arrays is typically done using sound field representation in terms of orthogonal basis functions (spherical/cylindrical harmonics). In this paper, an alternative sound field representation in terms of plane waves is described, and a method for estimating it directly from measurements at microphones is proposed. It is shown that representing a field as a collection of plane waves arriving from various directions simplifies source localization, beamforming, and spatial audio playback. A comparison of the new method with the well-known spherical harmonics based beamforming algorithm is done, and it is shown that both algorithms can be expressed in the same framework but with weights computed differently. It is also shown that the proposed method can be extended to cylindrical arrays. A number of features important for the design and operation of spherical microphone arrays in real applications are revealed. Results indicate that it is possible to reconstruct the sound scene up to order p with p2 microphones spherical array.},
	keywords = {Acoustic fields, acoustic position measurement, acoustic signal processing, acoustic waves, acoustical scene analysis, array signal processing, circular arrays, cylindrical microphone arrays, direction-independent acoustic behavior, microphone arrays, orthogonal basis functions, plane-wave decomposition, Position measurement, signal reconstruction, sound field reconstruction, sound field representation, source localization, spatial audio playback, spherical harmonics based beamforming algorithm, spherical microphone arrays},
	isbn = {1558-7916},
	doi = {10.1109/TASL.2009.2022000},
	author = {Zotkin,Dmitry N and Duraiswami, Ramani and Gumerov, Nail A.}
}
@conference {18477,
	title = {Imaging concert hall acoustics using visual and audio cameras},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing, 2008. ICASSP 2008},
	year = {2008},
	month = {2008///},
	pages = {5284 - 5287},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Using a developed real time audio camera, that uses the output of a spherical microphone array beamformer steered in all directions to create central projection to create acoustic intensity images, we present a technique to measure the acoustics of rooms and halls. A panoramic mosaiced visual image of the space is also create. Since both the visual and the audio camera images are central projection, registration of the acquired audio and video images can be performed using standard computer vision techniques. We describe the technique, and apply it to the examine the relation between acoustical features and architectural details of the Dekelbaum concert hall at the Clarice Smith Performing Arts Center in College Park, MD.},
	keywords = {Acoustic imaging, acoustic intensity images, acoustic measurement, Acoustic measurements, Acoustic scattering, acoustic signal processing, acoustical camera, acoustical scene analysis, acquired audio registration, audio cameras, audio signal processing, CAMERAS, central projection, Computer vision, Educational institutions, HUMANS, image registration, Image segmentation, imaging concert hall acoustics, Layout, microphone arrays, panoramic mosaiced visual image, Raman scattering, reverberation, room acoustics, spherical microphone array beamformer, spherical microphone arrays, video image registration, visual cameras},
	isbn = {978-1-4244-1483-3},
	doi = {10.1109/ICASSP.2008.4518852},
	author = {O{\textquoteright}Donovan,A. and Duraiswami, Ramani and Zotkin,Dmitry N}
}
@conference {18483,
	title = {Sound field decomposition using spherical microphone arrays},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing, 2008. ICASSP 2008},
	year = {2008},
	month = {2008///},
	pages = {277 - 280},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Spherical microphone arrays offer a number of attractive properties such as direction-independent acoustic behavior and ability to reconstruct the sound field in the vicinity of the array. Such ability is necessary in applications such as ambisonics and recreating auditory environment over headphones. We compare the performance of two scene reconstruction algorithms - one based on least-squares fitting the observed potentials and another based on computing the far-field signature function directly from the microphone measurements. A number of features important for the design and operation of spherical microphone arrays in real applications are revealed. Results indicate that it is possible to reconstruct the sound scene up to order p with p2 microphones.},
	keywords = {Acoustic applications, Acoustic arrays, Acoustic fields, acoustic position measurement, Acoustic propagation, acoustic signal processing, acoustic waves, array signal processing, Equations, far-field signature function, Layout, least-squares fitting, microphone arrays, scene reconstruction algorithms, Signal processing algorithms, sound field decomposition, spherical microphone arrays, Surface acoustic waves},
	isbn = {978-1-4244-1483-3},
	doi = {10.1109/ICASSP.2008.4517600},
	author = {Zotkin,Dmitry N and Duraiswami, Ramani and Gumerov, Nail A.}
}
@conference {18480,
	title = {Frequency Independent Flexible Spherical Beamforming Via Rbf Fitting},
	booktitle = {2006 IEEE International Conference on Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings},
	volume = {5},
	year = {2006},
	month = {2006/05//},
	pages = {V-V - V-V},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We describe a new method for sound analysis using a spherical microphone array without the use of quadrature over the sphere. Quadrature based solutions are very sensitive to the placement of microphones on the sphere, needing measurements to be made at exactly the quadrature positions. We propose to use fitting with band-limited radial basis functions (RBFs) rather than quadrature. Our approach results in frequency independent beamformer weights for flexibly placed microphone locations. Results are demonstrated using both synthetic and real spherical array data},
	keywords = {acoustic signal processing, array signal processing, band-limited radial basis functions, Computer science, Educational institutions, Eigenvalues and eigenfunctions, Equations, Frequency, frequency independent beamformer weights, frequency independent flexible spherical beamforming, microphone arrays, Nails, Position measurement, RBF fitting, Robustness, sound analysis, spherical array data, spherical microphone array},
	isbn = {1-4244-0469-X},
	doi = {10.1109/ICASSP.2006.1661208},
	author = {Yerukhimovich,A. and Duraiswami, Ramani and Gumerov, Nail A. and Zotkin,Dmitry N}
}
@conference {14522,
	title = {Plane-wave decomposition analysis for spherical microphone arrays},
	booktitle = {IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2005},
	year = {2005},
	month = {2005/10//},
	pages = {150 - 153},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Spherical microphone arrays have attracted attention for analyzing the sound field in a region and beamforming. The analysis of the recorded sound has been performed in terms of spherical wave-functions, and recently the use of plane-wave expansions has been suggested. We show that the plane-wave basis is intimately related to the spherical wave-functions. Reproduction in terms of both representations satisfies certain band-limit criteria. We provide an error bound that shows that to reproduce the spatial characteristics of a sound of a certain frequency we need to be able to accurately represent sounds of up to a particular order, which establishes a Nyquist-like criterion. The order of the sound field in turn is related to the number of microphones in the array necessary to achieve accurate quadrature on the sphere. These results are illustrated with simulations.},
	keywords = {Acoustic propagation, Acoustic scattering, acoustic signal processing, acoustic waves, array signal processing, band-limit criteria, beamforming, Educational institutions, Fourier transforms, Frequency, Laboratories, microphone arrays, Nails, Nyquist criterion, Nyquist-like criterion, Partial differential equations, plane-wave decomposition analysis, sound field analysis, spherical microphone arrays, spherical wave-functions},
	isbn = {0-7803-9154-3},
	doi = {10.1109/ASPAA.2005.1540191},
	author = {Duraiswami, Ramani and Zhiyun Li and Zotkin,Dmitry N and Grassi,E. and Gumerov, Nail A.}
}
@article {18462,
	title = {Processing of reverberant speech for time-delay estimation},
	journal = {IEEE Transactions on Speech and Audio Processing},
	volume = {13},
	year = {2005},
	month = {2005/11//},
	pages = {1110 - 1118},
	abstract = {In this paper, we present a method of extracting the time-delay between speech signals collected at two microphone locations. Time-delay estimation from microphone outputs is the first step for many sound localization algorithms, and also for enhancement of speech. For time-delay estimation, speech signals are normally processed using short-time spectral information (either magnitude or phase or both). The spectral features are affected by degradations in speech caused by noise and reverberation. Features corresponding to the excitation source of the speech production mechanism are robust to such degradations. We show that these source features can be extracted reliably from the speech signal. The time-delay estimate can be obtained using the features extracted even from short segments (50-100 ms) of speech from a pair of microphones. The proposed method for time-delay estimation is found to perform better than the generalized cross-correlation (GCC) approach. A method for enhancement of speech is also proposed using the knowledge of the time-delay and the information of the excitation source.},
	keywords = {Acoustic noise, acoustic signal processing, array signal processing, data mining, Degradation, delay estimation, Feature extraction, Hilbert envelope, localization algorithm, microphone arrays, microphone location, Microphones, Phase estimation, reverberation, short-time spectral information, Signal processing, source features, source information excitation, speech enhancement, Speech processing, speech production mechanism, speech signal, time-delay, time-delay estimation},
	isbn = {1063-6676},
	doi = {10.1109/TSA.2005.853005},
	author = {Yegnanarayana,B. and Prasanna,S. R.M and Duraiswami, Ramani and Zotkin,Dmitry N}
}
@conference {18461,
	title = {Efficient evaluation of reverberant sound fields},
	booktitle = {Applications of Signal Processing to Audio and Acoustics, 2001 IEEE Workshop on the},
	year = {2001},
	month = {2001///},
	pages = {203 - 206},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {An image method due to Allen and Berkley (1979) is often used to simulate the effect of reverberation in rooms. This method is relatively expensive computationally. We present a fast method for conducting such simulations using multipole expansions. For M real and image sources and N evaluation points, while the image method requires O(MN) operations, our method achieves the calculations in O(M + N) operations, resulting in a substantial speedup. Applications of our technique are also expected in simulation of virtual audio},
	keywords = {AB algorithm, acoustic signal processing, architectural acoustics, audio signal processing, Computational modeling, Computer interfaces, Computer simulation, Educational institutions, image method, image sources, Impedance, Laboratories, microphone arrays, multipole expansions, Nails, performance evaluation, reverberant sound fields, reverberation, room reverberation, simulation, Simulations, speedup, virtual audio},
	isbn = {0-7803-7126-7},
	doi = {10.1109/ASPAA.2001.969578},
	author = {Duraiswami, Ramani and Gumerov, Nail A. and Zotkin,Dmitry N and Davis, Larry S.}
}
@conference {18468,
	title = {Multimodal 3-D tracking and event detection via the particle filter},
	booktitle = {IEEE Workshop on Detection and Recognition of Events in Video, 2001. Proceedings},
	year = {2001},
	month = {2001///},
	pages = {20 - 27},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Determining the occurrence of an event is fundamental to developing systems that can observe and react to them. Often, this determination is based on collecting video and/or audio data and determining the state or location of a tracked object. We use Bayesian inference and the particle filter for tracking moving objects, using both video data obtained from multiple cameras and audio data obtained using arrays of microphones. The algorithms developed are applied to determining events arising in two fields of application. In the first, the behavior of a flying echo locating bat as it approaches a moving prey is studied, and the events of search, approach and capture are detected. In a second application we describe detection of turn-taking in a conversation between possibly moving participants recorded using a smart video conferencing setup},
	keywords = {algorithms, APPROACH, audio data collection, audio signal processing, Bayesian inference, Bayesian methods, belief networks, CAMERAS, capture, conversation, echo, Educational institutions, Event detection, event occurrence, filtering theory, flying echo locating bat behaviour, Image motion analysis, inference mechanisms, Laboratories, microphone arrays, moving object tracking, moving participants, moving prey, multimodal 3D tracking, multiple cameras, Object detection, particle filter, Particle filters, Particle tracking, Robustness, search, smart video conferencing setup, target tracking, Teleconferencing, tracking filters, turn-taking detection, video data collection, video signal processing},
	isbn = {0-7695-1293-3},
	doi = {10.1109/EVENT.2001.938862},
	author = {Zotkin,Dmitry N and Duraiswami, Ramani and Davis, Larry S.}
}
