In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence.
This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided.
The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.
Table of Contents
Chapter 1 A Joint Introduction To Natural Language Processing And To Deep Learning
Chapter 2 Deep Learning In Conversational Language Understanding
Chapter 3 Deep Learning In Spoken And Text-Based Dialog Systems
Chapter 4 Deep Learning In Lexical Analysis And Parsing
Chapter 5 Deep Learning In Knowledge Graph
Chapter 6 Deep Learning In Machine Translation
Chapter 7 Deep Learning In Question Answering
Chapter 8 Deep Learning In Sentiment Analysis
Chapter 9 Deep Learning In Social Computing
Chapter 10 Deep Learning In Natural Language Generation From Images
Chapter 11 Epilogue: Frontiers Of Nlp In The Deep Learning Era