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» Hierarchical Hidden Markov Models for Information Extraction
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ICRA
2006
IEEE
202views Robotics» more  ICRA 2006»
15 years 7 months ago
Primitive Communication based on Motion Recognition and Generation with Hierarchical Mimesis Model
— Communication skill is essential for social robots in various environments such as homes, offices, and hospitals, where the robots are expected to interact with humans. In thi...
Wataru Takano, Katsu Yamane, Tomomichi Sugihara, K...
CORR
2000
Springer
129views Education» more  CORR 2000»
15 years 1 months ago
Prosody-Based Automatic Segmentation of Speech into Sentences and Topics
A crucial step in processing speech audio data for information extraction, topic detection, or browsing/playback is to segment the input into sentence and topic units. Speech segm...
Elizabeth Shriberg, Andreas Stolcke, Dilek Z. Hakk...
GECCO
2003
Springer
130views Optimization» more  GECCO 2003»
15 years 6 months ago
Extracting Test Sequences from a Markov Software Usage Model by ACO
The aim of the paper is to investigate methods for deriving a suitable set of test paths for a software system. The design and the possible uses of the software system are modelled...
Karl Doerner, Walter J. Gutjahr
ICASSP
2011
IEEE
14 years 5 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...
ICML
2007
IEEE
16 years 2 months ago
Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
Kai Ni, Lawrence Carin, David B. Dunson