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» A Spectral Algorithm for Learning Hidden Markov Models
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JMLR
2010
152views more  JMLR 2010»
13 years 2 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
ICASSP
2011
IEEE
12 years 11 months ago
HNM-based MFCC+F0 extractor applied to statistical speech synthesis
Currently, the statistical framework based on Hidden Markov Models (HMMs) plays a relevant role in speech synthesis, while voice conversion systems based on Gaussian Mixture Model...
Daniel Erro, Iñaki Sainz, Eva Navas, Inma H...
TASLP
2010
157views more  TASLP 2010»
13 years 2 months ago
HMM-Based Reconstruction of Unreliable Spectrographic Data for Noise Robust Speech Recognition
This paper presents a framework for efficient HMM-based estimation of unreliable spectrographic speech data. It discusses the role of Hidden Markov Models (HMMs) during minimum mea...
Bengt J. Borgstrom, Abeer Alwan
NIPS
2004
13 years 9 months ago
Blind One-microphone Speech Separation: A Spectral Learning Approach
We present an algorithm to perform blind, one-microphone speech separation. Our algorithm separates mixtures of speech without modeling individual speakers. Instead, we formulate ...
Francis R. Bach, Michael I. Jordan
NIPS
2007
13 years 9 months ago
Agreement-Based Learning
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
Percy Liang, Dan Klein, Michael I. Jordan