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Results 1 - 10
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10,136
The Hierarchical Hidden Markov Model: Analysis and Applications
- MACHINE LEARNING
, 1998
"... . We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our model is motivated by the complex multi-scale structure which appears in many natural sequences, particularly in langua ..."
Abstract
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Cited by 326 (3 self)
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. We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our model is motivated by the complex multi-scale structure which appears in many natural sequences, particularly
Hierarchical Hidden Markov Models (HHMMs)
"... HHMM structure; pattern recognition; motion analysis. The objective of this paper is to automatically build a Hierarchical Hidden Markov Model (HHMM) (Fine et al., 1998) structure to detect semantic patterns from data with an unknown structure by exploring the natural hierarchical decomposition embe ..."
Abstract
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HHMM structure; pattern recognition; motion analysis. The objective of this paper is to automatically build a Hierarchical Hidden Markov Model (HHMM) (Fine et al., 1998) structure to detect semantic patterns from data with an unknown structure by exploring the natural hierarchical decomposition
USING HIERARCHICAL HIDDEN MARKOV MODELS
, 2003
"... Structure elements in a time sequence (e.g. video) are repetitive segments with consistent deterministic or stochastic characteristics. While most existing work in detecting structurs follow a supervised paradigm, we propose a fully unsupervised statistical solution in this paper. We present a unifi ..."
Abstract
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unified approach to structure discovery from long video sequences as simultaneously finding the statistical descriptions of structure and locating segments that matches the descriptions. We model the multilevel statistical structure as hierarchical hidden Markov models, and present efficient algorithms
Hierarchical Hidden Markov Models with General State Hierarchy
- IN AAAI 2004
, 2004
"... The hierarchical hidden Markov model (HHMM) is an extension of the hidden Markov model to include a hierarchy of the hidden states. This form of hierarchical modeling has been found useful in applications such as handwritten character recognition, behavior recognition, video indexing, and text ..."
Abstract
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Cited by 41 (13 self)
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The hierarchical hidden Markov model (HHMM) is an extension of the hidden Markov model to include a hierarchy of the hidden states. This form of hierarchical modeling has been found useful in applications such as handwritten character recognition, behavior recognition, video indexing, and text
Hierarchical Hidden Markov Models for Information Extraction
"... Information extraction can be defined as the task of automatically extracting instances of specified classes or relations from text. We consider the case of using machine learning methods to induce models for extracting relation instances from biomedical articles. We propose and evaluate an approach ..."
Abstract
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Cited by 60 (0 self)
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an approach that is based on using hierarchical hidden Markov models to represent the grammatical structure of the sentences being processed. Our approach first uses a shallow parser to construct a multi-level representation of each sentence being processed. Then we train hierarchical HMMs to capture
Hierarchical Hidden Markov Model for Rushes Structuring and Indexing
"... Abstract. Rushes footage are considered as cheap gold mine with the potential for reuse in broadcasting and filmmaking industries. However, it is difficult to mine the “gold ” from the rushes since usually only minimum metadata is available. This paper focuses on the structuring and indexing of the ..."
Abstract
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Cited by 1 (0 self)
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of the rushes to facilitate mining and retrieval of “gold”. We present a new approach for rushes structuring and indexing based on motion feature. We model the problem by a two-level Hierarchical Hidden Markov Model (HHMM). The HHMM, on one hand, represents the semantic concepts in its higher level to provide
Melodic Analysis using Hierarchical Hidden Markov Models
"... This dissertation attempts to show that hierarchical hidden Markov models (HHMMs) can be used effectively to model mid-level musical structures. Using data taken from chorales composed by Johann Sebastian Bach, a number of models were designed and trained to reflect elements of phrase-level and bar- ..."
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This dissertation attempts to show that hierarchical hidden Markov models (HHMMs) can be used effectively to model mid-level musical structures. Using data taken from chorales composed by Johann Sebastian Bach, a number of models were designed and trained to reflect elements of phrase-level and bar
Learning Profiles based on Hierarchical Hidden Markov Model
"... Abstract. This paper presents a method for automatically constructing a sophisticated user/process profile from traces of user/process behavior. User profile is encoded by means of a Hierarchical Hidden Markov Model (HHMM). The HHMM is a well formalized tool suitable to model complex patterns in lon ..."
Abstract
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Cited by 1 (0 self)
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Abstract. This paper presents a method for automatically constructing a sophisticated user/process profile from traces of user/process behavior. User profile is encoded by means of a Hierarchical Hidden Markov Model (HHMM). The HHMM is a well formalized tool suitable to model complex patterns
LEARNING MUSICAL PITCH STRUCTURES WITH HIERARCHICAL HIDDEN MARKOV MODELS
"... In this paper we attempt to demonstrate the strengths of Hierarchical Hidden Markov Models (HHMMs) in the representation and modelling of musical structures. We show how relatively simple HHMMs, containing a minimum of expert knowledge, use their advantage of having multiple layers to perform well o ..."
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In this paper we attempt to demonstrate the strengths of Hierarchical Hidden Markov Models (HHMMs) in the representation and modelling of musical structures. We show how relatively simple HHMMs, containing a minimum of expert knowledge, use their advantage of having multiple layers to perform well
Learning Hierarchical Hidden Markov Models for Video Structure Discovery
, 2002
"... Structure elements in a time sequence are repetitive segments that bear consistent deterministic or stochastic characteristics. While most existing work in detecting structures follow a supervised paradigm, we propose a fully unsupervised statistical solution in this paper. We present a unified appr ..."
Abstract
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Cited by 13 (6 self)
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approach to structure discovery from long video sequences as simultaneously finding the statistical descriptions of structure and locating segments that matches the descriptions. We model the multilevel statistical structure as hierarchical hidden Markov models, and present efficient algorithms
Results 1 - 10
of
10,136
