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A key resource for machine learning and speech recognition researchers and engineers, Large Margin and Kernel Methods for Speech Recognition unites research related to speech and speaker recognition based on recent advances in large margin and kernel methods. The first part of the book presents theoretical and practical foundations, from support vector machines to large margin methods for structured learning. The second part is dedicated to acoustic modeling of continuous speech recognizers. The third part introduces large margin methods for discriminative language modeling. The last part of the book discusses applications of speaker verification and identification.