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Robust Speech Recognition and Understanding
Edited by Michael Grimm and Kristian Kroschel, ISBN 978-3-902613-08-0, Hard cover, 460 pages, Publisher: I-Tech Education and Publishing, Published: June 01, 2007 under CC BY-NC-SA 3.0 license, in subject Artificial Intelligence
This book on Robust Speech Recognition and Understanding brings together many different aspects of the current research on automatic speech recognition and language understanding. The first four chapters address the task of voice activity detection which is considered an important issue for all speech recognition systems. The next chapters give several extensions to state-of-the-art HMM methods. Furthermore, a number of chapters particularly address the task of robust ASR under noisy conditions. Two chapters on the automatic recognition of a speaker's emotional state highlight the importance of natural speech understanding and interpretation in voice-driven systems. The last chapters of the book address the application of conversational systems on robots, as well as the autonomous acquisition of vocalization skills.
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Book contents
- Chapter 1Voice Activity Detection. Fundamentals and Speech Recognition System Robustness
- Chapter 2Bimodal Emotion Recognition using Speech and Physiological Changes
- Chapter 3Emotion Estimation in Speech Using a 3D Emotion Space Concept
- Chapter 4Linearly Interpolated Hierarchical N-gram Language Models for Speech Recognition Engines
- Chapter 5A Factored Language Model for Prosody Dependent Speech Recognition
- Chapter 6Early Decision Making in Continuous Speech
- Chapter 7Analysis and Implementation of an Automated Delimiter of "Quranic" Verses in Audio Files using Speech Recognition Techniques
- Chapter 8An Improved GA Based Modified Dynamic Neural Network for Cantonese-Digit Speech Recognition
- Chapter 9Talking Robot and the Autonomous Acquisition of Vocalization and Singing Skill
- Chapter 10Conversation System of an Everyday Robot Robovie-IV
- Chapter 11Sound Localization of Elevation using Pinnae for Auditory Robots
- Chapter 12Autocorrelation-based Methods for Noise-Robust Speech Recognition
- Chapter 13The Research of Noise-Robust Speech Recognition Based on Frequency Warping Wavelet
- Chapter 14Uncertainty in Signal Estimation and Stochastic Weighted Viterbi Algorithm: A Unified Framework to Address Robustness in Speech Recognition and Speaker Verification
- Chapter 15Novel Approaches to Speech Detection in the Processing of Continuous Audio Streams
- Chapter 16New Advances in Voice Activity Detection using HOS and Optimization Strategies
- Chapter 17Voice and Noise Detection with AdaBoost
- Chapter 18Evolutionary Speech Recognition
- Chapter 19Using Genetic Algorithm to Improve the Performance of Speech Recognition Based on Artificial Neural Network
- Chapter 20A General Approximation-Optimization Approach to Large Margin Estimation of HMMs
- Chapter 21Double Layer Architectures for Automatic Speech Recognition Using HMM
- Chapter 22Audio Visual Speech Recognition and Segmentation Based on DBN Models
- Chapter 23Discrete-Mixture HMMs-based Approach for Noisy Speech Recognition
- Chapter 24Speech Recognition in Unknown Noisy Conditions
- Chapter 25Speech Recognition Under Noise Conditions: Compensation Methods
