@article {14023,
	title = {Speaker Localization Using Excitation Source Information in Speech},
	journal = {Speech and Audio Processing, IEEE Transactions on},
	volume = {13},
	year = {2005},
	month = {2005/09//},
	pages = {751 - 761},
	abstract = {This paper presents the results of simulation and real room studies for localization of a moving speaker using information about the excitation source of speech production. The first step in localization is the estimation of time-delay from speech collected by a pair of microphones. Methods for time-delay estimation generally use spectral features that correspond mostly to the shape of vocal tract during speech production. Spectral features are affected by degradations due to noise and reverberation. This paper proposes a method for localizing a speaker using features that arise from the excitation source during speech production. Experiments were conducted by simulating different noise and reverberation conditions to compare the performance of the time-delay estimation and source localization using the proposed method with the results obtained using the spectrum-based generalized cross correlation (GCC) methods. The results show that the proposed method shows lower number of discrepancies in the estimated time-delays. The bias, variance and the root mean square error (RMSE) of the proposed method is consistently equal or less than the GCC methods. The location of a moving speaker estimated using the time-delays obtained by the proposed method are closer to the actual values, than those obtained by the GCC method.},
	keywords = {correlation, correlation;, cross, Delay, error, error;, estimation;, excitation, generalized, information;, localization;, mean, methods;, processing;, production;, root, source, speaker, speech, square, TIME},
	isbn = {1063-6676},
	doi = {10.1109/TSA.2005.851907},
	author = {Raykar,V.C. and Yegnanarayana,B. and Prasanna,S. R.M and Duraiswami, Ramani}
}
@article {18167,
	title = {Anti-collusion fingerprinting for multimedia},
	journal = {Signal Processing, IEEE Transactions on},
	volume = {51},
	year = {2003},
	month = {2003/04//},
	pages = {1069 - 1087},
	abstract = {Digital fingerprinting is a technique for identifying users who use multimedia content for unintended purposes, such as redistribution. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cost-effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are combined to disrupt the underlying fingerprints. We investigate the problem of designing fingerprints that can withstand collusion and allow for the identification of colluders. We begin by introducing the collusion problem for additive embedding. We then study the effect that averaging collusion has on orthogonal modulation. We introduce a tree-structured detection algorithm for identifying the fingerprints associated with K colluders that requires O(Klog(n/K)) correlations for a group of n users. We next develop a fingerprinting scheme based on code modulation that does not require as many basis signals as orthogonal modulation. We propose a new class of codes, called anti-collusion codes (ACCs), which have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we can therefore identify groups of K or fewer colluders. We present a construction of binary-valued ACC under the logical AND operation that uses the theory of combinatorial designs and is suitable for both the on-off keying and antipodal form of binary code modulation. In order to accommodate n users, our code construction requires only O( radic;n) orthogonal signals for a given number of colluders. We introduce three different detection strategies that can be used with our ACC for identifying a suspect set of colluders. We demonstrate the performance of our ACC for fingerprinting multimedia and identifying colluders through experiments using Gaussian signals and real images.},
	keywords = {(mathematics);, additive, algorithm;, and, anti-collusion, attack;, averaging, binary, code, codes;, codevectors;, coding;, colluders, collusion;, combinatorial, communication;, compression;, correlation;, cost-effective, data, data;, design, DETECTION, detection;, digital, embedding;, fingerprinting;, Gaussian, identification;, image, images;, keying;, logical, mathematics;, Modulation, modulation;, multimedia, multimedia;, of, on-off, operation;, orthogonal, processes;, real, redistribution;, Security, signal, signals;, theory;, tree-structured, TREES, watermarking;},
	isbn = {1053-587X},
	doi = {10.1109/TSP.2003.809378},
	author = {Trappe,W. and M. Wu and Wang,Z.J. and Liu,K. J.R}
}
