Matches in SemOpenAlex for { <https://semopenalex.org/work/W2078304724> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W2078304724 endingPage "709" @default.
- W2078304724 startingPage "704" @default.
- W2078304724 abstract "Recently, speech scientists have been motivated by the great, success of building margin-based classifiers, and have thus proposed novel methods to estimate continuous-density hidden Markov model (HMM) for automatic speech recognition (ASR) according to the notion that the decision boundaries determined by the estimated HMMs attain the maximum classification margin as in learning support vector machines. Although a good performance has been observed, the margin used in the ASR community is often specified as a parameter that has no explicit relationship with the HMM parameters. The issues of how the margin is related to the HMM parameters and how it directly characterises the generalisation capability of HMM-based classifiers have not been addressed so far in the community. In this study, the authors attempt to formulate the margin used in the soft margin estimation framework as a function of the HMM parameters. The key idea is to relate the standard distance-based margin with the concept of divergence among competing HMM state Gaussian mixture model densities. Experimental results show that the proposed model-based margin function is a good indication about the quality of HMMs on a given ASR task without the conventional needs of running experiments extensively using a separate set of test samples." @default.
- W2078304724 created "2016-06-24" @default.
- W2078304724 creator A5029670581 @default.
- W2078304724 creator A5066868860 @default.
- W2078304724 creator A5079659476 @default.
- W2078304724 date "2013-10-01" @default.
- W2078304724 modified "2023-09-27" @default.
- W2078304724 title "Model‐based margin estimation for hidden Markov model learning and generalisation" @default.
- W2078304724 cites W111968546 @default.
- W2078304724 cites W2033178790 @default.
- W2078304724 cites W2105440194 @default.
- W2078304724 cites W2110467295 @default.
- W2078304724 cites W2111479622 @default.
- W2078304724 cites W2111492050 @default.
- W2078304724 cites W2115415333 @default.
- W2078304724 cites W2139212933 @default.
- W2078304724 cites W2150142469 @default.
- W2078304724 cites W2151484683 @default.
- W2078304724 cites W2156060302 @default.
- W2078304724 cites W2158289097 @default.
- W2078304724 cites W2159112514 @default.
- W2078304724 cites W4243847155 @default.
- W2078304724 cites W53977603 @default.
- W2078304724 cites W98828706 @default.
- W2078304724 doi "https://doi.org/10.1049/iet-spr.2013.0036" @default.
- W2078304724 hasPublicationYear "2013" @default.
- W2078304724 type Work @default.
- W2078304724 sameAs 2078304724 @default.
- W2078304724 citedByCount "1" @default.
- W2078304724 countsByYear W20783047242017 @default.
- W2078304724 crossrefType "journal-article" @default.
- W2078304724 hasAuthorship W2078304724A5029670581 @default.
- W2078304724 hasAuthorship W2078304724A5066868860 @default.
- W2078304724 hasAuthorship W2078304724A5079659476 @default.
- W2078304724 hasConcept C105795698 @default.
- W2078304724 hasConcept C11413529 @default.
- W2078304724 hasConcept C119857082 @default.
- W2078304724 hasConcept C153180895 @default.
- W2078304724 hasConcept C154945302 @default.
- W2078304724 hasConcept C159886148 @default.
- W2078304724 hasConcept C162324750 @default.
- W2078304724 hasConcept C163836022 @default.
- W2078304724 hasConcept C187736073 @default.
- W2078304724 hasConcept C23224414 @default.
- W2078304724 hasConcept C33923547 @default.
- W2078304724 hasConcept C41008148 @default.
- W2078304724 hasConcept C774472 @default.
- W2078304724 hasConcept C96250715 @default.
- W2078304724 hasConcept C98763669 @default.
- W2078304724 hasConceptScore W2078304724C105795698 @default.
- W2078304724 hasConceptScore W2078304724C11413529 @default.
- W2078304724 hasConceptScore W2078304724C119857082 @default.
- W2078304724 hasConceptScore W2078304724C153180895 @default.
- W2078304724 hasConceptScore W2078304724C154945302 @default.
- W2078304724 hasConceptScore W2078304724C159886148 @default.
- W2078304724 hasConceptScore W2078304724C162324750 @default.
- W2078304724 hasConceptScore W2078304724C163836022 @default.
- W2078304724 hasConceptScore W2078304724C187736073 @default.
- W2078304724 hasConceptScore W2078304724C23224414 @default.
- W2078304724 hasConceptScore W2078304724C33923547 @default.
- W2078304724 hasConceptScore W2078304724C41008148 @default.
- W2078304724 hasConceptScore W2078304724C774472 @default.
- W2078304724 hasConceptScore W2078304724C96250715 @default.
- W2078304724 hasConceptScore W2078304724C98763669 @default.
- W2078304724 hasIssue "8" @default.
- W2078304724 hasLocation W20783047241 @default.
- W2078304724 hasOpenAccess W2078304724 @default.
- W2078304724 hasPrimaryLocation W20783047241 @default.
- W2078304724 hasRelatedWork W2039473210 @default.
- W2078304724 hasRelatedWork W2118728396 @default.
- W2078304724 hasRelatedWork W2131524408 @default.
- W2078304724 hasRelatedWork W2157200163 @default.
- W2078304724 hasRelatedWork W2350115929 @default.
- W2078304724 hasRelatedWork W2569579427 @default.
- W2078304724 hasRelatedWork W2793260526 @default.
- W2078304724 hasRelatedWork W3129972734 @default.
- W2078304724 hasRelatedWork W4313547211 @default.
- W2078304724 hasRelatedWork W4313547478 @default.
- W2078304724 hasVolume "7" @default.
- W2078304724 isParatext "false" @default.
- W2078304724 isRetracted "false" @default.
- W2078304724 magId "2078304724" @default.
- W2078304724 workType "article" @default.