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Proceedings Paper

Speaker recognition using neural network and adaptive wavelet transform
Author(s): Mohammad Bodruzzaman; Xingkang Li; Kah Eng Kuah; Lamar Crowder; Mohan Malkani; Harold H. Szu; Brian A. Telfer
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Paper Abstract

The same word uttered by different people has different waveforms. It has also been observed that the same word uttered by the same person has different waveform at different times. This difference can be characterized by some time domain dilation effects in the waveform. In our experiment a set of words was selected and each word was uttered eight times by five different speakers. The objective of this work is to extract a wavelet basis function for the speech data generated by each individual speaker. The wavelet filter coefficients are then used as a feature set and fed into a neural network-based speaker recognition system. This is an attempt to cascade a wavelet network (wavenet) and a neural network (neural-net) for feature extraction and classification respectively and applied for speaker recognition. The results show very high promise and good prospects to couple a wavelet network and neural networks.

Paper Details

Date Published: 27 August 1993
PDF: 10 pages
Proc. SPIE 1961, Visual Information Processing II, (27 August 1993); doi: 10.1117/12.150976
Show Author Affiliations
Mohammad Bodruzzaman, Tennessee State Univ. (United States)
Xingkang Li, Tennessee State Univ. (United States)
Kah Eng Kuah, Tennessee State Univ. (United States)
Lamar Crowder, Tennessee State Univ. (United States)
Mohan Malkani, Tennessee State Univ. (United States)
Harold H. Szu, Naval Surface Warfare Ctr. (United States)
Brian A. Telfer, Naval Surface Warfare Ctr. (United States)


Published in SPIE Proceedings Vol. 1961:
Visual Information Processing II
Friedrich O. Huck; Richard D. Juday, Editor(s)

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