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» Experimental Evaluation of Hierarchical Hidden Markov Models
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ICASSP
2011
IEEE
14 years 5 months ago
A unified approach to real time audio-to-score and audio-to-audio alignment using sequential Montecarlo inference techniques
We present a methodology for the real time alignment of music signals using sequential Montecarlo inference techniques. The alignment problem is formulated as the state tracking o...
Nicola Montecchio, Arshia Cont
SIGIR
1999
ACM
15 years 6 months ago
The Decomposition of Human-Written Summary Sentences
We define the problem of decomposing human-written summary sentences and propose a novel Hidden Markov Model solution to the problem. Human summarizers often rely on cutting and ...
Hongyan Jing, Kathleen McKeown
INTERSPEECH
2010
14 years 8 months ago
Incremental word learning using large-margin discriminative training and variance floor estimation
We investigate incremental word learning in a Hidden Markov Model (HMM) framework suitable for human-robot interaction. In interactive learning, the tutoring time is a crucial fac...
Irene Ayllón Clemente, Martin Heckmann, Ale...
ICIP
2003
IEEE
16 years 3 months ago
Feature selection for unsupervised discovery of statistical temporal structures in video
We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
Lexing Xie, Shih-Fu Chang, Ajay Divakaran, Huifang...
ROMAN
2007
IEEE
127views Robotics» more  ROMAN 2007»
15 years 8 months ago
Incremental on-line hierarchical clustering of whole body motion patterns
Abstract— This paper describes a novel algorithm for autonomous and incremental learning of motion pattern primitives by observation of human motion. Human motion patterns are ed...
Dana Kulic, Wataru Takano, Yoshihiko Nakamura