DocumentCode
2363531
Title
Automatic speech segmentation using neural tree networks
Author
Sharma, Manish ; Mammone, Richard
Author_Institution
CAIP Center, Rutgers Univ., Piscataway, NJ, USA
fYear
1995
fDate
31 Aug-2 Sep 1995
Firstpage
282
Lastpage
290
Abstract
Segmentation of speech into sub-word acoustic units using neural tree networks (NTNs) is presented. NTN is a hierarchical classifier that combines the properties of both decision trees and feedforward neural networks. The number of sub-word acoustic units in a given speech segment may or may not be known to the segmentation algorithm. Both these varieties of speech segmentation problems are addressed. The performance of the speech segmentation algorithm using NTN is compared to that obtained using hidden Markov models (HMMs) and dynamic programming-based approach proposed elsewhere
Keywords
decision theory; feedforward neural nets; speech processing; speech recognition; trees (mathematics); decision trees; feedforward neural networks; hierarchical classifier; neural tree networks; speech recognition; speech segmentation; Algorithm design and analysis; Classification tree analysis; Decision trees; Feedforward neural networks; Feedforward systems; Hidden Markov models; Neural networks; Speech processing; Speech recognition; Vocabulary;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Signal Processing [1995] V. Proceedings of the 1995 IEEE Workshop
Conference_Location
Cambridge, MA
Print_ISBN
0-7803-2739-X
Type
conf
DOI
10.1109/NNSP.1995.514902
Filename
514902
Link To Document