Speech enhancement based on Hilbert-Huang transform
| Autor: | Zhenpeng Liao, Zhuo-Fu Liu, En-Fang Sang |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
business.industry
Speech recognition Mode (statistics) Pattern recognition Hilbert spectral analysis Computer Science::Numerical Analysis Signal Hilbert–Huang transform Data set Speech enhancement Nonlinear system Computer Science::Systems and Control Artificial intelligence Noise removal business Mathematics |
| Zdroj: | 2005 International Conference on Machine Learning and Cybernetics. |
| DOI: | 10.1109/icmlc.2005.1527807 |
| Popis: | The newly developed Hilbert-Huang transform (HHT) is introduced briefly in this paper. The HHT method is specially developed for analyzing nonlinear and non-stationary data. The method consists of two parts: (1) the empirical mode decomposition (EMD), and (2) the Hilbert spectral analysis. The EMD, which is the first part of the theory, can decompose any complicated data set into a finite and often small numbers of intrinsic mode functions (IMFs). IMFs also thus admit well-behaved Hilbert transforms. The law of its EMD and characteristics of the IMFs of a speech signal with unwanted sound are studied. Based on these studies, a new noise removal method has been developed. In the application, the HHT has been used to enhance the performance of speech signals by removing unwanted sound. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|