Influence of initialisation and stop criteria on HMM based recognisers
Electronics Letters, ISSN: 0013-5194, Vol: 36, Issue: 13, Page: 1165-1166
2000
- 18Citations
- 5Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
A study is presented into the importance of two commonly overlooked factors influencing generalisation ability in the field of hidden Markov model (HMM) based recogniser training algorithms by means of a comparative study of four initialisation methods and three stop criteria in different applications. The results show that better results have been found with the equal-occupancy initialisation method and the fixed-threshold stop criterion.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=0033703849&origin=inward; http://dx.doi.org/10.1049/el:20000826; http://digital-library.theiet.org/doi/10.1049/el%3A20000826; http://dx.doi.org/10.1049/el%3A20000826; https://dx.doi.org/10.1049/el%3A20000826; https://www.crossref.org/iPage?doi=10.1049%2Fel%3A20000826
Institution of Engineering and Technology (IET)
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