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SPEECH
2010
136views more  SPEECH 2010»
15 years 5 months ago
Robust speech recognition by integrating speech separation and hypothesis testing
Missing data methods attempt to improve robust speech recognition by distinguishing between reliable and unreliable data in the time-frequency domain. Such methods require a binar...
Soundararajan Srinivasan, DeLiang L. Wang
TASLP
2011
15 years 1 months ago
Advances in Missing Feature Techniques for Robust Large-Vocabulary Continuous Speech Recognition
— Missing feature theory (MFT) has demonstrated great potential for improving the noise robustness in speech recognition. MFT was mostly applied in the log-spectral domain since ...
Maarten Van Segbroeck, Hugo Van Hamme
INFOCOM
2012
IEEE
13 years 9 months ago
Robust multi-pipeline scheduling in low-duty-cycle wireless sensor networks
—Data collection is one of the major traffic pattern in wireless sensor networks, which requires regular source nodes to send data packets to a common sink node with limited end...
Yongle Cao, Shuo Guo, Tian He
TVCG
2012
196views Hardware» more  TVCG 2012»
13 years 9 months ago
Robust Morse Decompositions of Piecewise Constant Vector Fields
—In this paper, we introduce a new approach to computing a Morse decomposition of a vector field on a triangulated manifold surface. The basic idea is to convert the input vector...
Andrzej Szymczak, Eugene Zhang
DATAMINE
2006
127views more  DATAMINE 2006»
15 years 6 months ago
Computing LTS Regression for Large Data Sets
Least trimmed squares (LTS) regression is based on the subset of h cases (out of n) whose least squares t possesses the smallest sum of squared residuals. The coverage h may be se...
Peter Rousseeuw, Katrien van Driessen