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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Narita, M. Shimamura, T. |
| Copyright Year | 2011 |
| Description | Author affiliation: Graduate School of Science and Engineering, Saitama University, 255, Shimo-Okubo, Sakura-ku, 338-8570 JAPAN (Narita, M.; Shimamura, T.) |
| Abstract | The fundamental frequency extraction of speech is an important problem needed in many speech processing systems. In this paper, we propose a new method for extracting the fundamental frequency of noisy speech using correlation, difference, and exponent. The inverse Fourier transform of the exponentiated amplitude spectrum is weighted by the inverse of the average exponentiated magnitude difference function. By using an appropriate exponent constant determined from the noise amount, the signal component corresponding to the fundamental frequency is emphasized. We compare the proposed method with conventional ones. The simulation results obtained with the appropriate exponent at each signal-to-noise ratio show the effectiveness of the proposed method. |
| Starting Page | 342 |
| Ending Page | 346 |
| File Size | 773311 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467307529 |
| e-ISBN | 9781467307536 |
| e-ISBN | 9781467307512 |
| DOI | 10.1109/ISSPIT.2011.6151585 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-12-14 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Average Magnitude Difference Function Fundamental Frequency Weighted Autocorrelation Autocorrelation |
| Content Type | Text |
| Resource Type | Article |
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