This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. 

This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.

This book comprehensively presents an unconventional quantum criticality caused by valence fluctuations, which offers theoretical understanding of unconventional Fermi-liquid properties in cerium- and ytterbium-based heavy fermion metals including CeCu2(Si,Ge)2 and CeRhIn5 under pressure, and quasicrystal β-YbAlB4 and Yb15Al34Au51.

The book begins with an introduction to fundamental concepts for heavy fermion systems, valence fluctuation, and quantum phase transition, including self-consistent renormalization group theory. A subsequent chapter is devoted to a comprehensive description of the theory of the unconventional quantum criticality based on a valence transition, featuring explicit temperature dependence of various physical quantities, which allows for comparisons to relevant experiments. Lastly, it discusses how ubiquitous the valence fluctuation is, presenting candidate materials not only in heavy fermions, but also in strongly correlated electrons represented by high-Tc superconductor cuprates.

Introductory chapters provide useful materials for learning fundamentals of heavy fermion systems and their theory. Further, experimental topics relevant to valence fluctuations are valuable resources for those who are new to the field to easily catch up with experimental background and facts.

This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. 

This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.

This book comprehensively presents an unconventional quantum criticality caused by valence fluctuations, which offers theoretical understanding of unconventional Fermi-liquid properties in cerium- and ytterbium-based heavy fermion metals including CeCu2(Si,Ge)2 and CeRhIn5 under pressure, and quasicrystal β-YbAlB4 and Yb15Al34Au51.

The book begins with an introduction to fundamental concepts for heavy fermion systems, valence fluctuation, and quantum phase transition, including self-consistent renormalization group theory. A subsequent chapter is devoted to a comprehensive description of the theory of the unconventional quantum criticality based on a valence transition, featuring explicit temperature dependence of various physical quantities, which allows for comparisons to relevant experiments. Lastly, it discusses how ubiquitous the valence fluctuation is, presenting candidate materials not only in heavy fermions, but also in strongly correlated electrons represented by high-Tc superconductor cuprates.

Introductory chapters provide useful materials for learning fundamentals of heavy fermion systems and their theory. Further, experimental topics relevant to valence fluctuations are valuable resources for those who are new to the field to easily catch up with experimental background and facts.