Two-level recognition of isolated word using neural nets
dc.contributor.author | Howard, Ian | |
dc.contributor.author | Huckvale, MA | |
dc.date.accessioned | 2019-10-22T12:51:42Z | |
dc.date.available | 2019-10-22T12:51:42Z | |
dc.date.issued | 1989-12-01 | |
dc.identifier.issn | 0537-9989 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/15039 | |
dc.description.abstract |
This paper describes a neural-net based isolated word recogniser that has a better performance on a standard multi-speaker database than our reference Hidden Markov Model recogniser. The complete neural net recogniser is formed from two parts: a front-end which transforms the complex acoustic specification of the speech into a simplified phonetic feature specification, and a whole-word discriminator net. Each level was trained separately, thus considerably reducing the time necessary to train the overall system. | |
dc.format.extent | 90-94 | |
dc.language.iso | en | |
dc.title | Two-level recognition of isolated word using neural nets | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.issue | 313 | |
plymouth.publication-status | Published | |
plymouth.journal | IEE Conference Publication | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dc.rights.embargoperiod | Not known | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |