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ORCIDTechniques for Noise Robustness in Automatic Speech Recognition 2012
- Tuomas Virtanen, Rita Singh, Bhiksha Raj:
Techniques for Noise Robustness in Automatic Speech Recognition. Wiley 2012, ISBN 978-1-119-97088-0 - Tuomas Virtanen, Rita Singh, Bhiksha Raj:
Introduction. 1-5 - Rita Singh, Bhiksha Raj, Tuomas Virtanen:
The Basics of Automatic Speech Recognition. 7-30 - Bhiksha Raj, Tuomas Virtanen, Rita Singh:
The Problem of Robustness in Automatic Speech Recognition. 31-50 - Rainer Martin
, Dorothea Kolossa:
Voice Activity Detection, Noise Estimation, and Adaptive Filters for Acoustic Signal Enhancement. 51-85 - Paris Smaragdis:
Extraction of Speech from Mixture Signals. 87-108 - John W. McDonough, Ken'ichi Kumatani:
Microphone Arrays. 109-157 - Matthias Wölfel:
From Signals to Speech Features by Digital Signal Processing. 159-192 - Richard M. Stern, Nelson Morgan:
Features Based on Auditory Physiology and Perception. 193-227 - Jasha Droppo:
Feature Compensation. 229-250 - Reinhold Haeb-Umbach, Alexander Krueger:
Reverberant Speech Recognition. 251-281 - Yannick Estève, Paul Deléglise:
Adaptation and Discriminative Training of Acoustic Models. 283-310 - John R. Hershey, Steven J. Rennie, Jonathan Le Roux:
Factorial Models for Noise Robust Speech Recognition. 311-345 - Michael L. Seltzer:
Acoustic Model Training for Robust Speech Recognition. 347-368 - Jon Barker:
Missing-Data Techniques: Recognition with Incomplete Spectrograms. 369-398 - Jort Florent Gemmeke, Ulpu Remes:
Missing-Data Techniques: Feature Reconstruction. 399-432 - Arun Narayanan, DeLiang Wang:
Computational Auditory Scene Analysis and Automatic Speech Recognition. 433-462 - Hank Liao:
Uncertainty Decoding. 463-486
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