We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...
In this paper, we propose a neural network model for predicting the durations of syllables. A four layer feedforward neural network trained with backpropagation algorithm is used ...
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
The design of computer architectures requires the setting of multiple parameters on which the final performance depends. The number of possible combinations make an extremely huge ...
Pedro A. Castillo, Antonio Miguel Mora, Juan Juli&...