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...
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...
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...
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...
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...