How to Build a Speech Recognition Application
Author: Bruce Balentine
Publisher:
Published: 1999
Total Pages: 0
ISBN-13: 9780967127811
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Voice Application Development for Android
Author: Michael F. McTear
Publisher: Packt Publishing Ltd
Published: 2013-12-11
Total Pages: 192
ISBN-13: 1783285303
DOWNLOAD EBOOKThis book will give beginners an introduction to building voice-based applications on Android. It will begin by covering the basic concepts and will build up to creating a voice-based personal assistant. By the end of this book, you should be in a position to create your own voice-based applications on Android from scratch in next to no time.Voice Application Development for Android is for all those who are interested in speech technology and for those who, as owners of Android devices, are keen to experiment with developing voice apps for their devices. It will also be useful as a starting point for professionals who are experienced in Android application development but who are not familiar with speech technologies and the development of voice user interfaces. Some background in programming in general, particularly in Java, is assumed.
Intelligent Speech Signal Processing
Author: Nilanjan Dey
Publisher: Academic Press
Published: 2019-04-02
Total Pages: 210
ISBN-13: 0128181303
DOWNLOAD EBOOKIntelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multidisciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, development and management of intelligent systems, neural networks and related machine learning techniques for speech signal processing.
Robust Speech Recognition in Embedded Systems and PC Applications
Author: Jean-Claude Junqua
Publisher: Springer Science & Business Media
Published: 2006-04-18
Total Pages: 193
ISBN-13: 0306470276
DOWNLOAD EBOOKRobust Speech Recognition in Embedded Systems and PC Applications provides a link between the technology and the application worlds. As speech recognition technology is now good enough for a number of applications and the core technology is well established around hidden Markov models many of the differences between systems found in the field are related to implementation variants. We distinguish between embedded systems and PC-based applications. Embedded applications are usually cost sensitive and require very simple and optimized methods to be viable. Robust Speech Recognition in Embedded Systems and PC Applications reviews the problems of robust speech recognition, summarizes the current state of the art of robust speech recognition while providing some perspectives, and goes over the complementary technologies that are necessary to build an application, such as dialog and user interface technologies. Robust Speech Recognition in Embedded Systems and PC Applications is divided into five chapters. The first one reviews the main difficulties encountered in automatic speech recognition when the type of communication is unknown. The second chapter focuses on environment-independent/adaptive speech recognition approaches and on the mainstream methods applicable to noise robust speech recognition. The third chapter discusses several critical technologies that contribute to making an application usable. It also provides some design recommendations on how to design prompts, generate user feedback and develop speech user interfaces. The fourth chapter reviews several techniques that are particularly useful for embedded systems or to decrease computational complexity. It also presents some case studies for embedded applications and PC-based systems. Finally, the fifth chapter provides a future outlook for robust speech recognition, emphasizing the areas that the author sees as the most promising for the future. Robust Speech Recognition in Embedded Systems and PC Applications serves as a valuable reference and although not intended as a formal University textbook, contains some material that can be used for a course at the graduate or undergraduate level. It is a good complement for the book entitled Robustness in Automatic Speech Recognition: Fundamentals and Applications co-authored by the same author.
Automatic Speech Recognition
Author: Dong Yu
Publisher: Springer
Published: 2014-11-11
Total Pages: 329
ISBN-13: 1447157796
DOWNLOAD EBOOKThis book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.
Deep Learning with Applications Using Python
Author: Navin Kumar Manaswi
Publisher: Apress
Published: 2018-04-04
Total Pages: 228
ISBN-13: 1484235169
DOWNLOAD EBOOKExplore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. What You Will Learn Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn. Use face recognition and face detection capabilities Create speech-to-text and text-to-speech functionality Engage with chatbots using deep learning Who This Book Is For Data scientists and developers who want to adapt and build deep learning applications.
Robust Automatic Speech Recognition
Author: Jinyu Li
Publisher: Academic Press
Published: 2015-10-30
Total Pages: 308
ISBN-13: 0128026162
DOWNLOAD EBOOKRobust 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 - The first book that provides a comprehensive review on noise and reverberation robust speech recognition methods in the era of deep neural networks - Connects robust speech recognition techniques to machine learning paradigms with rigorous mathematical treatment - Provides elegant and structural ways to categorize and analyze noise-robust speech recognition techniques - Written by leading researchers who have been actively working on the subject matter in both industrial and academic organizations for many years
The Human-Computer Interaction Handbook
Author: Andrew Sears
Publisher: CRC Press
Published: 2007-09-19
Total Pages: 1386
ISBN-13: 1410615863
DOWNLOAD EBOOKThis second edition of The Human-Computer Interaction Handbook provides an updated, comprehensive overview of the most important research in the field, including insights that are directly applicable throughout the process of developing effective interactive information technologies. It features cutting-edge advances to the scientific
Voice Enabling Web Applications
Author: Ken Abbott
Publisher: Apress
Published: 2008-01-01
Total Pages: 252
ISBN-13: 1430208503
DOWNLOAD EBOOKDevelopers can use the same technology to build both automated voice services as well as visual Web sites, and Ken Abbott shows how in this comprehensive introduction to the syntax, concepts and strategies relevant to VoiceXML.
The Application of Hidden Markov Models in Speech Recognition
Author: Mark Gales
Publisher: Now Publishers Inc
Published: 2008
Total Pages: 125
ISBN-13: 1601981201
DOWNLOAD EBOOKThe Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.
