Abstract
Present day commercial automatic speech recognition (ASR) systems still pale in comparison to the human ability to recognize speech. For decades, people tried to mimic biology for machine recognition tasks and ASR is no exception. Widely used and accepted Mel Frequency Cepstral Coefficients, for example, try to develop better filter banks by looking at the distribution of the hair cells along the basilar membrane. However, all these approaches stem only from topological and anatomical considerations. This research proposes to take this biological inspiration one step further by imitating some of the dynamical computation of our auditory system via describing a biologically plausible algorithm that exclusively utilizes spikes in both the feature extraction and recognition stages. The prototype biological system is demonstrated on voiced phonemes and preliminary results show competitive recognition performance on a vowel dataset in the presence of noise. © 2006 IEEE.
Recommended Citation
I. Uysal et al., "A Biologically Plausible System Approach For Noise Robust Vowel Recognition," Midwest Symposium on Circuits and Systems, vol. 1, pp. 245 - 249, article no. 4267120, Institute of Electrical and Electronics Engineers, Dec 2006.
The definitive version is available at https://doi.org/10.1109/MWSCAS.2006.382043
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
978-142440173-4
International Standard Serial Number (ISSN)
1548-3746
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Dec 2006
