Speech Recognition and Understanding

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Title Page
Copyright
DECLARATION
ABOUT THE EDITOR
TABLE OF CONTENTS
List of Contributors
List of Abbreviations
Preface
Section 1: Methods and Approaches for Speech Recognition
	Chapter 1 Artificial Intelligence for Speech Recognition Based on Neural Networks
		Abstract
		Introduction
		Pattern Recognition
		Neural Networks
		Procedure Works
		Conclusion
		References
	Chapter 2 An HMM-Like Dynamic Time Warping Scheme for Automatic Speech Recognition
		Abstract
		Introduction
		Speech Recognition By DTW
		The Proposed Hmm-Like DTW Approach for Speech Recognition
		Hmm-Like DTW
		Experiments And Results
		Conclusions
		References
	Chapter 3 Direct Recovery of Clean Speech Using a Hybrid Noise Suppression Algorithm for Robust Speech Recognition System
		Abstract
		Introduction
		System Model
		Algorithm Description
		Algorithm Evaluation
		Conclusion
		Supplementary Materials
		References
	Chapter 4 Deep Neural Learning Adaptive Sequential Monte Carlo for Automatic Image and Speech Recognition
		Abstract
		Introduction
		Materials and Methods
		Results and Discussion
		Conclusions
		Acknowledgments
		References
	Chapter 5 A Fast Learning Method for Multilayer Perceptrons in Automatic Speech Recognition Systems
		Abstract
		Introduction
		A Fast Learning Method
		Experiments
		Conclusions
		Acknowledgments
		References
Section 2: Speech Recognition for Different Languages
	Chapter 6 Development of Application Specific Continuous Speech Recognition System in Hindi
		Abstract
		Introduction
		Automatic Speech Recognition System
		The Training Methodology
		Evaluation Methodology
		Results And Discussion
		Conclusion And Future Work
		References
	Chapter 7 Multitask Learning with Local Attention for Tibetan Speech Recognition
		Abstract
		Introduction
		Related Work
		Methods
		Experiments
		Conclusions
		Authors’ Contributions
		Acknowledgments
		References
	Chapter 8 Arabic Speech Recognition System Based on MFCC and HMMs
		Introduction
		Mel Frequency Cepstral Coefficients (Mfcc)
		Hidden Markov Model (Hmm)
		Experimental Results
		Conclusion
		References
	Chapter 9 Using Morphological Data in Language Modeling for Serbian Large Vocabulary Speech Recognition
		Abstract
		Introduction
		Relevant Previous Work
		Materials And Methods
		Results And Discussion
		Conclusions
		Data Availability
		Acknowledgments
		References
	Chapter 10 Phoneme Sequence Modeling in the Context of Speech Signal Recognition in Language “Baoule”
		Abstract
		Introduction
		The Speech Signals
		System Overview
		Hidden Markov Model Discrete Time
		Implementation
		Conclusions
		Annexes
		References
Section 3: Applications with Speech Recognition
	Chapter 11 An Overview of Basics Speech Recognition and Autonomous Approach for Smart Home IOT Low Power Devices
		Abstract
		Introduction
		Overview State of the Art
		Our Methodology
		Algorithm Description
		Recognition Technique
		Results
		Conclusion
		References
	Chapter 12 BigEar: Ubiquitous Wireless Low-Budget Speech Capturing Interface
		Abstract
		Introduction
		Related Work
		Bigear Architecture
		Speech Acquisition Model and Implementation
		Speech Reconstruction
		Bigear Simulation and Model Validation
		Experimental Results and Evaluation
		Conclusions and Future Works
		References
	Chapter 13 Using Speech Recognition in Learning Primary School Mathematics via Explain, Instruct and Facilitate Techniques
		Abstract
		Introduction
		Materials and Methods
		Results and Discussions
		Conclusions and Recommendations
		Acknowledgements
		References
	Chapter 14 A Prototype of a Semantic Platform with a Speech Recognition System for Visual Impaired People
		Abstract
		Introduction
		Review of Literature
		Current Problems of Web Platforms for Accessibility
		Prototype of Semantic Platform with Speech Recognition System
		Conceptual Scheme of Architecture
		Expected Contributions and Future Work
		References
Section 4: Language Understanding Technology
	Chapter 15 English Sentence Recognition Based on HMM and Clustering
		Abstract
		Introduction
		Whole Design Process
		Core Algorithm
		Experimental Results and Analysis
		Conclusion
		Acknowledgements
		References
	Chapter 16 A Comparative Study to Understanding about Poetics Based on Natural Language Processing
		Abstract
		Introduction
		Materials and Method
		Results
		Discussion
		Conclusion
		References
	Chapter 17 Semi-Supervised Learning of Statistical Models for Natural Language Understanding
		Abstract
		Introduction
		Related Work
		The Proposed Framework
		Experimental Results
		Conclusions
		Acknowledgments
		References
	Chapter 18 Linguistic Factors Influencing Speech Audiometric Assessment
		Abstract
		Introduction
		Linguistic Cues to Speech Understanding
		Aim And Research Questions
		Syntactic Complexity, Cognitive Load, and Speech Understanding
		The Role of Open Versus Closed Word Classes In Sentence Understanding
		Materials and Method
		Results
		Discussion
		Conclusion
		Acknowledgments
		References
Index
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