A Logical Hierarchical Hidden Semi-Markov Model for Team Intention Recognition
نویسندگان
چکیده
منابع مشابه
The Hierarchical Dirichlet Process Hidden Semi-Markov Model Citation
There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the traditional HMM. However, in many settings the HDP-HMM’s strict Markovian constraints are undesirable, particularly if we wish to learn or encode non-geometric state durations. We can extend the HDP-HMM to capture such structure by drawing upon explicit...
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There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the traditional HMM. However, in many settings the HDP-HMM’s strict Markovian constraints are undesirable, particularly if we wish to learn or encode non-geometric state durations. We can extend the HDP-HMM to capture such structure by drawing upon explicit...
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Given a set of sequential data in an unsupervised setting, we often aim to infer meaningful states present in the data along with characteristics that describe and distinguish those states. For example, in a speaker diarization (or who-spoke-when) problem, we are given a single audio recording of a meeting and wish to infer the number of speakers present, when they speak, and some characteristi...
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ژورنال
عنوان ژورنال: Discrete Dynamics in Nature and Society
سال: 2015
ISSN: 1026-0226,1607-887X
DOI: 10.1155/2015/975951