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ER
2008
Springer
107views Database» more  ER 2008»
14 years 11 months ago
A Conceptual Modeling Framework for Expressing Observational Data Semantics
Observational data (i.e., data that records observations and measurements) plays a key role in many scientific disciplines. Observational data, however, are typically structured an...
Shawn Bowers, Joshua S. Madin, Mark P. Schildhauer
112
Voted
INTERSPEECH
2010
14 years 4 months ago
Hidden Markov models with context-sensitive observations for grapheme-to-phoneme conversion
Hidden Markov models (HMMs) have proven useful in various aspects of speech technology from automatic speech recognition through speech synthesis, speech segmentation and grapheme...
Udochukwu Kalu Ogbureke, Peter Cahill, Julie Carso...
EPIA
2005
Springer
15 years 3 months ago
Acquiring Observation Models Through Reverse Plan Monitoring
We present a general-purpose framework for updating a robot’s observation model within the context of planning and execution. Traditional plan execution relies on monitoring plan...
Sonia Chernova, Elisabeth Crawford, Manuela M. Vel...
JUCS
2002
101views more  JUCS 2002»
14 years 9 months ago
Modelling Agents as Observable Sources
Abstract: Observation is a fundamental interaction pattern in today's computerbased systems. Adopting observation as the main modelling criterion, computer-based systems can b...
Mirko Viroli, Andrea Omicini
87
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ICASSP
2011
IEEE
14 years 1 months ago
Learning and inference algorithms for partially observed structured switching vector autoregressive models
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Balakrishnan Varadarajan, Sanjeev Khudanpur