Title :
Automatic speech segmentation using neural tree networks
Author :
Sharma, Manish ; Mammone, Richard
Author_Institution :
CAIP Center, Rutgers Univ., Piscataway, NJ, USA
fDate :
31 Aug-2 Sep 1995
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;
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
DOI :
10.1109/NNSP.1995.514902