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Computer and Information Science » Artificial Intelligence
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, Chapters published June 01, 2007 under CC BY-NC-SA 3.0 license
DOI: 10.5772/46211
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.
- Chapter 1
Voice Activity Detection. Fundamentals and Speech Recognition System Robustness - Chapter 2
Novel Approaches to Speech Detection in the Processing of Continuous Audio Streams - Chapter 3
New Advances in Voice Activity Detection using HOS and Optimization Strategies - Chapter 4
Voice and Noise Detection with AdaBoost - Chapter 5
Evolutionary Speech Recognition - Chapter 6
Using Genetic Algorithm to Improve the Performance of Speech Recognition Based on Artificial Neural Network - Chapter 7
A General Approximation-Optimization Approach to Large Margin Estimation of HMMs - Chapter 8
Double Layer Architectures for Automatic Speech Recognition Using HMM - Chapter 9
Audio Visual Speech Recognition and Segmentation Based on DBN Models - Chapter 10
Discrete-Mixture HMMs-based Approach for Noisy Speech Recognition - Chapter 11
Speech Recognition in Unknown Noisy Conditions - Chapter 12
Uncertainty in Signal Estimation and Stochastic Weighted Viterbi Algorithm: A Unified Framework to Address Robustness in Speech Recognition and Speaker Verification - Chapter 13
The Research of Noise-Robust Speech Recognition Based on Frequency Warping Wavelet - Chapter 14
Autocorrelation-based Methods for Noise-Robust Speech Recognition - Chapter 15
Bimodal Emotion Recognition using Speech and Physiological Changes - Chapter 16
Emotion Estimation in Speech Using a 3D Emotion Space Concept - Chapter 17
Linearly Interpolated Hierarchical N-gram Language Models for Speech Recognition Engines - Chapter 18
A Factored Language Model for Prosody Dependent Speech Recognition - Chapter 19
Early Decision Making in Continuous Speech - Chapter 20
Analysis and Implementation of an Automated Delimiter of "Quranic" Verses in Audio Files using Speech Recognition Techniques - Chapter 21
An Improved GA Based Modified Dynamic Neural Network for Cantonese-Digit Speech Recognition - Chapter 22
Talking Robot and the Autonomous Acquisition of Vocalization and Singing Skill - Chapter 23
Conversation System of an Everyday Robot Robovie-IV - Chapter 24
Sound Localization of Elevation using Pinnae for Auditory Robots - Chapter 25
Speech Recognition Under Noise Conditions: Compensation Methods
