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Content Provider | IEEE Xplore Digital Library |
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Author | Muthusamy, Y.K. Cole, R.A. Slaney, M. |
Copyright Year | 1990 |
Description | Author affiliation: Dept. of Comput. Sci. & Eng., Oregon Graduate Inst. of Sci. & Technol., Beaverton, OR, USA (Muthusamy, Y.K.; Cole, R.A.) |
Abstract | The ability of multilayer perceptrons (MLPs) trained with backpropagation to classify vowels excised from natural continuous speech is examined. Two spectral representations are compared: spectrograms and cochleagrams. The features used to train the MLPs include discrete Fourier transform (DFT) or cochleagram coefficients from a single frame in the middle of the vowel, or coefficients from each third of the vowel. The effects of estimates of pitch, duration, and the relative amplitude of the vowel were investigated. The experiments show that with coefficients alone, the cochleagram is superior to the spectrogram in classification performance for all experimental conditions. With the three additional features, however, the results are comparable. Perceptual experiments with trained human listeners on the same data revealed that MLPs perform much better than humans on vowels excised from context.< |
Starting Page | 533 |
Ending Page | 536 |
File Size | 419095 |
Page Count | 4 |
File Format | |
ISSN | 15206149 |
DOI | 10.1109/ICASSP.1990.115767 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1990-04-03 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Speech recognition Spectrogram Discrete Fourier transforms Humans Multilayer perceptrons Backpropagation Amplitude estimation |
Content Type | Text |
Resource Type | Article |
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