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SPEECH
2011
14 years 4 months ago
SNR loss: A new objective measure for predicting the intelligibility of noise-suppressed speech
Most of the existing intelligibility measures do not account for the distortions present in processed speech, such as those introduced by speech-enhancement algorithms. In the pre...
Jianfen Ma, Philipos C. Loizou
BMCBI
2004
181views more  BMCBI 2004»
14 years 9 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
KDD
2006
ACM
173views Data Mining» more  KDD 2006»
15 years 10 months ago
Robust information-theoretic clustering
How do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? Most clu...
Christian Böhm, Christos Faloutsos, Claudia P...
73
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ICASSP
2011
IEEE
14 years 1 months ago
Global variance modeling on frequency domain delta LSP for HMM-based speech synthesis
The speech parameter generation algorithm considering global variance (GV) for HMM-based speech synthesis proved to be effective against the over-smoothing problem. However, the c...
Shifeng Pan, Yoshihiko Nankaku, Keiichi Tokuda, Ji...
ICPR
2008
IEEE
15 years 4 months ago
A fuzzy c-means algorithm using a correlation metrics and gene ontology
A fuzzy c-means algorithm was adapted for analyzing microarray data. The adaptation consisted of initialization of fuzzy centroids using gene ontology information and the use of P...
Mingrui Zhang, Terry M. Therneau, Michael A. McKen...