Please use this identifier to cite or link to this item:
|Title:||Multilayer perceptron postprocessor to Hidden Markov modeling for speech recognition||Authors:||Jin, Guo
Chung, Lui Ho
|Issue Date:||1993||Citation:||Jin, Guo,Chung, Lui Ho (1993). Multilayer perceptron postprocessor to Hidden Markov modeling for speech recognition. Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing 2 : II-263. ScholarBank@NUS Repository.||Abstract:||In this paper, a new neural network postprocessor is introduced to enhance the classification capability of hidden Markov modeling for speech recognition. This postprocessor receives stimuli from not one but all word- HMMs for each word speech and does not require segmenting speech frames at subword level. A multilayer perceptron implementation has achieved 20% to 30% syllable error reduction in experiments reported here.||Source Title:||Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing||URI:||http://scholarbank.nus.edu.sg/handle/10635/111266||ISBN:||0780309464||ISSN:||07367791|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jul 19, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.