1. ScholarBank@NUS
  2. 1. Staff
  3. Staff Publications
Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/99489
DC FieldValue
dc.titleConnectionist architecture for all Mandarin syllables recognition
dc.contributor.authorPoo, Gee-Swee
dc.date.accessioned2014-10-27T06:04:38Z
dc.date.available2014-10-27T06:04:38Z
dc.date.issued1995
dc.identifier.citationPoo, Gee-Swee (1995). Connectionist architecture for all Mandarin syllables recognition. IEEE International Conference on Neural Networks - Conference Proceedings 4 : 2041-2045. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/99489
dc.description.abstractThis paper presents a modular connectionist architecture for all Mandarin syllables recognition. The technique used is based on the Time-Delay Neural Networks (TDNN). The architecture developed is capable of recognizing all 35 Finals, 21 Initials and 4 tones of the entire vocabulary of isolated Chinese syllables. Experimental results show a recognition accuracy of 93.9% for the Finals, 92.7% for the Initials and 99.3% for the tones, giving rise to an overall syllable recognition rate of about 90%.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentINFORMATION SYSTEMS & COMPUTER SCIENCE
dc.description.sourcetitleIEEE International Conference on Neural Networks - Conference Proceedings
dc.description.volume4
dc.description.page2041-2045
dc.description.codenICNNF
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.