Robust Speech Recognition of Uncertain or Missing Data: Theory and Applications

By Dorothea Kolossa

Chap. 1 - Introduction.-

Part I - Theoretical Foundations.-

Chap. 2 - Uncertainty Decoding and Conditional Bayesian Estimation.- Chap. 3 - Uncertainty Propagation.-

Part II - Applications.-

Chap. 4 - Front-End, Back-End, and Hybrid Techniques for Noise-Robust Speech Recognition.- Chap. 5 - Model-Based Approaches to Handling Uncertainty.- Chap. 6 - Reconstructing Noise-Corrupted Spectrographic Components for Robust Speech Recognition.- Chap. 7 - Automatic Speech Recognition Using Missing Data Techniques: Handling of Real-World Data.- Chap. 8 - Conditional Bayesian Estimation Employing a Phase-Sensitive Estimation Model for Noise-Robust Speech Recognition.-

Part III - Reverberation Robustness.-

Chap. 9 - Variance Compensation for Recognition of Reverberant Speech with Dereverberation Processing.- Chap. 10 - A Model-Based Approach to Joint Compensation of Noise and Reverberation for Speech Recognition.-

Part IV - Applications: Multiple Speakers and Modalities.-

Chap. 11 - Evidence Modelling for Missing Data Speech Recognition Using Small Microphone Arrays.- Chap. 12 - Recognition of Multiple Speech Sources Using ICA.- Chap. 13 - Use of Missing and Unreliable Data for Audiovisual Speech Recognition.-

Index.

• Format: Paperback
• Language: English
• ISBN: 3642438687
• ISBN13: 9783642438684
• Release Date: November 2014
• Publisher: Springer
• Length: 380 Pages
• Weight: 1.23 lbs.
• Dimensions: 0.8" x 6.1" x 9.2"