Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/99489
Title: Connectionist architecture for all Mandarin syllables recognition
Authors: Poo, Gee-Swee 
Issue Date: 1995
Source: Poo, Gee-Swee (1995). Connectionist architecture for all Mandarin syllables recognition. IEEE International Conference on Neural Networks - Conference Proceedings 4 : 2041-2045. ScholarBank@NUS Repository.
Abstract: This 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%.
Source Title: IEEE International Conference on Neural Networks - Conference Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/99489
Appears in Collections:Staff Publications

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

Page view(s)

21
checked on Mar 9, 2018

Google ScholarTM

Check


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