Compressive Sensing-Based Speech Enhancement
| Autor: | Jia-Ching Wang, Chang-Hong Lin, Shu-Fan Wang, Chung-Hsien Wu, Chih-Hao Shih, Yuan-Shan Lee |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Acoustics and Ultrasonics
business.industry Computer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing) 020206 networking & telecommunications Pattern recognition 02 engineering and technology Sparse approximation Speech enhancement 030507 speech-language pathology & audiology 03 medical and health sciences Computational Mathematics Noise Formant Compressed sensing Computer Science::Sound Frequency domain 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) Spectrogram Artificial intelligence Electrical and Electronic Engineering 0305 other medical science business Signal subspace Mathematics |
| Zdroj: | IEEE/ACM Transactions on Audio, Speech, and Language Processing. 24:2122-2131 |
| ISSN: | 2329-9304 2329-9290 |
| DOI: | 10.1109/taslp.2016.2598306 |
| Popis: | This study proposes a speech enhancement method based on compressive sensing. The main procedures involved in the proposed method are performed in the frequency domain. First, an overcomplete dictionary is constructed from the trained speech frames. The atoms of this redundant dictionary are spectrum vectors that are trained by the K-SVD algorithm to ensure the sparsity of the dictionary. For a noisy speech spectrum, formant detection and a quasi-SNR criterion are first utilized to determine whether a frequency bin in the spectrogram is reliable, and a corresponding mask is designed. The mask-extracted reliable components in a speech spectrum are regarded as partial observations and a measurement matrix is constructed. The problem can therefore be treated as a compressive sensing problem. The K atoms of a K-sparsity speech spectrum are found using an orthogonal matching pursuit algorithm. Because the K atoms form the speech signal subspace, the removal of the noise projected onto these K atoms is achieved by multiplying the noisy spectrum with the optimized gain that corresponds to each selected atom. The proposed method is experimentally compared with the baseline methods and demonstrates its superiority. |
| Databáze: | OpenAIRE |
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