Jinyu Li

Since I was a child, my father had me practice Chinese calligraphy every day. This was our family tradition, each generation since my great-grandfather lived by this tradition, because my great-great-grandfather named Li Zhenghua was a famous calligrapher in southern China. When I was a little older, my father found a brush painting teacher for me after seeing that I used chalk to draw all over the floor every day. Every week since then, I began to learn from him. This began my artistic journey of life in the Chinese brush painting. I love Chinese brush painting. The need to paint is just as if the need to live. So I have painted a lot. Deeply in my heart, I am very concerned about life, and painting for me is the record of my inner feelings of spiritual experiences. This album is an expression of culture and life through my brushes, a record of the major events of this era, and a cultural contribution to those who want to understand China.

Since I was a child, my father had me practice Chinese calligraphy every day. This was our family tradition, each generation since my great-grandfather lived by this tradition, because my great-great-grandfather named Li Zhenghua was a famous calligrapher in southern China. When I was a little older, my father found a brush painting teacher for me after seeing that I used chalk to draw all over the floor every day. Every week since then, I began to learn from him. This began my artistic journey of life in the Chinese brush painting. I love Chinese brush painting. The need to paint is just as if the need to live. So I have painted a lot. Deeply in my heart, I am very concerned about life, and painting for me is the record of my inner feelings of spiritual experiences. This album is an expression of culture and life through my brushes, a record of the major events of this era, and a cultural contribution to those who want to understand China.

Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that have been developed over the past thirty years, with an emphasis on practical methods that have been proven to be successful and which are likely to be further developed for future applications. The strengths and weaknesses of robustness-enhancing speech recognition techniques are carefully analyzed. The book covers noise-robust techniques designed for acoustic models which are based on both Gaussian mixture models and deep neural networks. In addition, a guide to selecting the best methods for practical applications is provided. The reader will: Gain a unified, deep and systematic understanding of the state-of-the-art technologies for robust speech recognition Learn the links and relationship between alternative technologies for robust speech recognition Be able to use the technology analysis and categorization detailed in the book to guide future technology development Be able to develop new noise-robust methods in the current era of deep learning for acoustic modeling in speech recognition