NDLI: New low rate wavelet models for the recognition of single spoken digits

Content Provider	IEEE Xplore Digital Library
Author	Karam, J.R. Phillips, W.J. Robertson, W.
Copyright Year	2000
Description	Author affiliation: Dept. of Eng. Math., Dalhousie Univ., Halifax, NS, Canada (Karam, J.R.)
Abstract	This paper describes three models acquired by applying various wavelet analysis techniques to subwords for the purpose of speaker independent single digit recognition. We emphasize the parameterization of the subwords according to a Mel scale in the cases of the sampled continuous wavelet transform (SCWT) and the wavelet packet decomposition (WPD). When using the discrete wavelet transform (DWT), a logarithmic segmentation is obtained and with it comes a very low parameter representation with a reduction of 3:1 when compared with the other two introduced models and with the Mel scale model. The DWT model has advantage over the other two due to its simplicity and fast implementation. Previous work by Phillips, Tosuner and Robertson (1995), based on preprocessing using traditional Fourier transform (FT) followed by a radial basis functions artificial neural network (RBF-ANN) yielded recognition in 90% range. Our results show that these new models outperformed the Mel scale model.
Starting Page	331
Ending Page	334
File Size	288026
Page Count	4
File Format	PDF
ISBN	0780359577
ISSN	08407789
DOI	10.1109/CCECE.2000.849724
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-05-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Continuous wavelet transforms Discrete wavelet transforms Wavelet transforms Frequency Fourier transforms Wavelet packets Sampling methods Mathematics Wavelet analysis Artificial neural networks
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

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