Hidden Markov models: an insight
Hidden Markov models (HMM) is a probabilistic model consisting of variables representing observations, variables that are hidden, the initial state distribution, transition matrix, and parameters for all observation distributions. The said model is commonly used in speech recognition field and it ha...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/56257/1/Hidden%20Markov%20models%20an%20insight.pdf |
| _version_ | 1796976441444794368 |
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| author | Mohd Yusoff, Mohd Izhan Mohamed, Ibrahim Abu Bakar, Mohd Rizam |
| author_facet | Mohd Yusoff, Mohd Izhan Mohamed, Ibrahim Abu Bakar, Mohd Rizam |
| author_sort | Mohd Yusoff, Mohd Izhan |
| collection | UPM |
| description | Hidden Markov models (HMM) is a probabilistic model consisting of variables representing observations, variables that are hidden, the initial state distribution, transition matrix, and parameters for all observation distributions. The said model is commonly used in speech recognition field and it has seen an increase in terms of usage, which include user profiling in mobile communication networks, and energy disaggregation. This paper shows, via numerical example, the computation of HMM's forward procedure will exceed the precision range of essentially any machine (even in double precision). It also extends the procedure to include Gaussian mixture hidden Markov models (GMHMM), the procedure that can be used as both a generator of observations, and as a model for how a given observation sequence was generated by an appropriate HMM. |
| first_indexed | 2024-03-06T09:25:52Z |
| format | Conference or Workshop Item |
| id | upm.eprints-56257 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T09:25:52Z |
| publishDate | 2014 |
| publisher | IEEE |
| record_format | dspace |
| spelling | upm.eprints-562572017-07-31T04:13:07Z http://psasir.upm.edu.my/id/eprint/56257/ Hidden Markov models: an insight Mohd Yusoff, Mohd Izhan Mohamed, Ibrahim Abu Bakar, Mohd Rizam Hidden Markov models (HMM) is a probabilistic model consisting of variables representing observations, variables that are hidden, the initial state distribution, transition matrix, and parameters for all observation distributions. The said model is commonly used in speech recognition field and it has seen an increase in terms of usage, which include user profiling in mobile communication networks, and energy disaggregation. This paper shows, via numerical example, the computation of HMM's forward procedure will exceed the precision range of essentially any machine (even in double precision). It also extends the procedure to include Gaussian mixture hidden Markov models (GMHMM), the procedure that can be used as both a generator of observations, and as a model for how a given observation sequence was generated by an appropriate HMM. IEEE 2014 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/56257/1/Hidden%20Markov%20models%20an%20insight.pdf Mohd Yusoff, Mohd Izhan and Mohamed, Ibrahim and Abu Bakar, Mohd Rizam (2014) Hidden Markov models: an insight. In: 6th International Conference on Information Technology and Multimedia (ICIMU 2014), 18-20 Nov. 2014, Putrajaya, Malaysia. (pp. 259-264). 10.1109/ICIMU.2014.7066641 |
| spellingShingle | Mohd Yusoff, Mohd Izhan Mohamed, Ibrahim Abu Bakar, Mohd Rizam Hidden Markov models: an insight |
| title | Hidden Markov models: an insight |
| title_full | Hidden Markov models: an insight |
| title_fullStr | Hidden Markov models: an insight |
| title_full_unstemmed | Hidden Markov models: an insight |
| title_short | Hidden Markov models: an insight |
| title_sort | hidden markov models an insight |
| url | http://psasir.upm.edu.my/id/eprint/56257/1/Hidden%20Markov%20models%20an%20insight.pdf |
| work_keys_str_mv | AT mohdyusoffmohdizhan hiddenmarkovmodelsaninsight AT mohamedibrahim hiddenmarkovmodelsaninsight AT abubakarmohdrizam hiddenmarkovmodelsaninsight |