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» Experimental Evaluation of Hierarchical Hidden Markov Models
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ICASSP
2009
IEEE
16 years 27 days ago
Trajectory training considering global variance for HMM-based speech synthesis
This paper presents a novel method for training hidden Markov models (HMMs) for use in HMM-based speech synthesis. The primary goal of HMM parameter optimization is to ensure that...
Tomoki Toda, Steve Young
IPM
2007
143views more  IPM 2007»
15 years 6 months ago
QCS: A system for querying, clustering and summarizing documents
Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particula...
Daniel M. Dunlavy, Dianne P. O'Leary, John M. Conr...
ICASSP
2009
IEEE
16 years 27 days ago
A variational EM algorithm for learning eigenvoice parameters in mixed signals
We derive an efficient learning algorithm for model-based source separation for use on single channel speech mixtures where the precise source characteristics are not known a pri...
Ron J. Weiss, Daniel P. W. Ellis
SDM
2012
SIAM
305views Data Mining» more  SDM 2012»
13 years 8 months ago
Learning Hierarchical Relationships among Partially Ordered Objects with Heterogeneous Attributes and Links
Objects linking with many other objects in an information network may imply various semantic relationships. Uncovering such knowledge is essential for role discovery, data cleanin...
Chi Wang, Jiawei Han, Qi Li, Xiang Li, Wen-Pin Lin...
HAPTICS
2002
IEEE
15 years 11 months ago
Building a Task Language for Segmentation and Recognition of User Input to Cooperative Manipulation Systems
We present the results of using Hidden Markov Models (HMMs) for automatic segmentation and recognition of user motions. Previous work on recognition of user intent with man/machin...
C. Sean Hundtofte, Gregory D. Hager, Allison M. Ok...