### Abstract

Fast estimation algorithms of Hidden Markov Models (HMMs), or alpha-HMMs, are presented. Such novel algorithms inherit speedup properties of the alpha-EM algorithm. Since the alpha-EM algorithm includes the traditional log-EM algorithm as its special case, the alpha-HMM also includes the traditional log-HMM as its special case. This generalization appears as the utilization of the past information which is the main device of the speedup. Since the memorization of the past information requires only little increase of computational load and memory, the iteration speedup directly appears as that of CPU time. Experimental results are given.

Original language | English |
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Title of host publication | IEEE Workshop on Statistical Signal Processing Proceedings |

Pages | 89-92 |

Number of pages | 4 |

DOIs | |

Publication status | Published - 2011 |

Event | 2011 IEEE Statistical Signal Processing Workshop, SSP 2011 - Nice Duration: 2011 Jun 28 → 2011 Jun 30 |

### Other

Other | 2011 IEEE Statistical Signal Processing Workshop, SSP 2011 |
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City | Nice |

Period | 11/6/28 → 11/6/30 |

### Fingerprint

### Keywords

- alpha-EM algorithm
- alpha-HMM
- past information
- speedup

### ASJC Scopus subject areas

- Electrical and Electronic Engineering
- Applied Mathematics
- Signal Processing
- Computer Science Applications

### Cite this

*IEEE Workshop on Statistical Signal Processing Proceedings*(pp. 89-92). [5967835] https://doi.org/10.1109/SSP.2011.5967835

**Fast estimation of Hidden Markov Models via alpha-EM algorithm.** / Matsuyama, Yasuo; Hayashi, Ryunosuke; Yokote, Ryota.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*IEEE Workshop on Statistical Signal Processing Proceedings.*, 5967835, pp. 89-92, 2011 IEEE Statistical Signal Processing Workshop, SSP 2011, Nice, 11/6/28. https://doi.org/10.1109/SSP.2011.5967835

}

TY - GEN

T1 - Fast estimation of Hidden Markov Models via alpha-EM algorithm

AU - Matsuyama, Yasuo

AU - Hayashi, Ryunosuke

AU - Yokote, Ryota

PY - 2011

Y1 - 2011

N2 - Fast estimation algorithms of Hidden Markov Models (HMMs), or alpha-HMMs, are presented. Such novel algorithms inherit speedup properties of the alpha-EM algorithm. Since the alpha-EM algorithm includes the traditional log-EM algorithm as its special case, the alpha-HMM also includes the traditional log-HMM as its special case. This generalization appears as the utilization of the past information which is the main device of the speedup. Since the memorization of the past information requires only little increase of computational load and memory, the iteration speedup directly appears as that of CPU time. Experimental results are given.

AB - Fast estimation algorithms of Hidden Markov Models (HMMs), or alpha-HMMs, are presented. Such novel algorithms inherit speedup properties of the alpha-EM algorithm. Since the alpha-EM algorithm includes the traditional log-EM algorithm as its special case, the alpha-HMM also includes the traditional log-HMM as its special case. This generalization appears as the utilization of the past information which is the main device of the speedup. Since the memorization of the past information requires only little increase of computational load and memory, the iteration speedup directly appears as that of CPU time. Experimental results are given.

KW - alpha-EM algorithm

KW - alpha-HMM

KW - past information

KW - speedup

UR - http://www.scopus.com/inward/record.url?scp=80052231399&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80052231399&partnerID=8YFLogxK

U2 - 10.1109/SSP.2011.5967835

DO - 10.1109/SSP.2011.5967835

M3 - Conference contribution

SN - 9781457705700

SP - 89

EP - 92

BT - IEEE Workshop on Statistical Signal Processing Proceedings

ER -