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» Learning Gaussian Process Models from Uncertain Data
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ICASSP
2011
IEEE
14 years 6 months ago
Sentence level emotion recognition based on decisions from subsentence segments
Emotion recognition from speech plays an important role in developing affective and intelligent systems. This study investigates sentence-level emotion recognition. We propose to ...
Je Hun Jeon, Rui Xia, Yang Liu
JFR
2006
88views more  JFR 2006»
15 years 2 months ago
Discovering natural kinds of robot sensory experiences in unstructured environments
We derive categories directly from robot sensor data to address the symbol grounding problem. Unlike model-based approaches where human intuitive correspondences are sought betwee...
Daniel H. Grollman, Odest Chadwicke Jenkins, Frank...
126
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UAI
2004
15 years 3 months ago
Dynamical Systems Trees
We propose dynamical systems trees (DSTs) as a flexible model for describing multiple processes that interact via a hierarchy of aggregating processes. DSTs extend nonlinear dynam...
Andrew Howard, Tony Jebara
NIPS
2007
15 years 3 months ago
Modeling Natural Sounds with Modulation Cascade Processes
Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences (∼1 s); phonemes (âˆ...
Richard Turner, Maneesh Sahani
PAMI
2008
161views more  PAMI 2008»
15 years 2 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...