65 search results - page 5 / 13 » Learning Spectral Clustering, With Application To Speech Sep... |
ICA
2012
Springer
12 years 1 months ago
2012
Springer
Non-negative spectrogram factorization algorithms such as probabilistic latent component analysis (PLCA) have been shown to be quite powerful for source separation. When training d...
ICA
2007
Springer
13 years 12 months ago
2007
Springer
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can b...
DATESO
2010
13 years 3 months ago
2010
Abstract. The high dimensionality of the data generated by social networks has been a big challenge for researchers. In order to solve the problems associated with this phenomenon,...
LREC
2008
13 years 7 months ago
2008
Based on simple methods such as observing word and part of speech tag co-occurrence and clustering, we generate syntactic parses of sentences in an entirely unsupervised and self-...
CORR
2008
Springer
13 years 5 months ago
2008
Springer
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...