Deep Learning for NLP and Speech Recognition

• Main Authors: Kamath, Uday (Author, http://id.loc.gov/vocabulary/relators/aut), Liu, John (http://id.loc.gov/vocabulary/relators/aut), Whitaker, James (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Subjects: Artificial intelligence.; Computational intelligence.; Python (Computer program language).; Artificial Intelligence.; Computational Intelligence.; Python.

With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights int...

Table of Contents:

• Notation xv
• Part 1: Machine Learning, NLP, and Speech Introduction
• Chapter 1 Introduction 1
• Chapter 2 Basics of Machine Learning 2
• Chapter 3 Text and Speech Basics 49
• Part 2: Deep Learning Basics
• Chapter 4 Basics of Deep Learning 105
• Chapter 5 Distributed Representations 213
• Chapter 6 Convolutional Neural Networks 275
• Chapter 7 Recurrent Neural Networks 329
• Chapter 8 Automatic Speech Recognition 387
• Part 3: Advance Deep Learning Techniques for Text and Speech
• Chapter 9 Attention and Memory Augmented Networks 429
• Chapter 10 Transfer learning: Scenarios, Self-Taught Learning, and Multitask Learning 485
• Chapter 11 Transfer Learning: Domain Adaptation 515
• Chapter 12 End-to-end Speech Recognition 559
• Chapter 13 Deep Reinforcement Learning for Text and Speech 601
• Future Outlook 647.