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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Molla, K.I. Hirose, K. Minematsu, N. |
| Copyright Year | 2008 |
| Description | Author affiliation: Grad. Sch. of Inf. Sci. & Technol., Univ. of Tokyo, Tokyo (Molla, K.I.; Hirose, K.) || Grad. Sch. of Eng., Univ. of Tokyo, Tokyo (Minematsu, N.) |
| Abstract | This paper presents a new method of periodic/non-periodic (P/nP) classification of noisy speech signals. Empirical mode decomposition (EMD), a newly developed tool to analyze nonlinear and non-stationary signals is used to filter the additive noise with the speech signal. The normalized autocorrelation of the filtered speech signal is computed to enhance the periodicity of the analyzing speech signal if any. It is considered that the voiced speech (with fundamental periodicity) signal is periodically correlated and the unvoiced signal is not. A noise robust P/nP decision rule is formulated based on third-order autocumulants of the autocorrelation function of speech signal. The experimental results show that the use of EMD improves the classification performance and the overall efficiency is noticeable as compared to other existing algorithms. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 578454 |
| Page Count | 5 |
| File Format | |
| ISBN | 9784885522321 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-10-14 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electronics, Information and Communication Engineers (IEICE) |
| Subject Keyword | Speech analysis Speech enhancement Signal analysis Autocorrelation Speech processing Speech synthesis Matching pursuit algorithms Noise robustness Spectral analysis Noise reduction voiced/unvoiced speech classification Empirical mode decomposition fundamental frequency higher-order spectral analysis periodic correlation speech denoising |
| Content Type | Text |
| Resource Type | Article |
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