This book discusses a large margin and kernel methods for speech recognition and speaker Speech and Speaker Recognition: Large Margin and Kernel Methods is an examination of research in the latest advances in large margin and kernel methods, as applied in the field of speech and speaker recognition. Key Features: Provides up-to-date snapshot of the current state of research in this area includes important aspects of extending binary support vector machines for speech recognition and speaker Discussing applications a large margin and kernel algorithms for sequence prediction methods required for modeling acoustic Reviews past and present work on discriminative training of language models, and explain the algorithms that are large margins for job applications part-of-speech tagging latest survey on the use of the kernel approach to text-independent speaker verification, and introduce the main concepts and algorithms work survey new kernel approach for learning the similarity matrix from data This book will appeal to researchers, practitioners, engineers, and scientists in the field machine processing of speech and learning.