Duong, Thanh Thi Hien and Nguyen, Phuong Cong and Nguyen, Cuong Quoc (2018) Exploiting Nonnegative Matrix Factorization with Mixed Group Sparsity Constraint to Separate Speech Signal from Single-channel Mixture with Unknown Ambient Noise. EAI Endorsed Transactions on Context-aware Systems and Applications, 4 (13): e5. ISSN 2409-0026
|
Text
eai.14-3-2018.154342.pdf - Published Version Available under License Creative Commons Attribution No Derivatives. Download (745kB) | Preview |
Abstract
This paper focuses on solving a challenging speech enhancement problem: improving the desired speech from a single-channel audio signal containing high-level unspecified noise (possibly environmental noise, music, other sounds, etc.). Using source separation technique, we investigate a solution combining nonnegative matrix factorization (NMF) with mixed group sparsity constraint that allows exploiting generic noise spectral model to guide the separation process. The experiment performed on a set of benchmarked audio signals with different types of real-world noise shows that the proposed algorithm yields better quantitative results in term of the signal-to-distortion ratio than the previously published algorithms.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Speech enhancement, source separation, nonnegative matrix factorizarion (NMF), sparsity constraint, generic source spectral model |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science QA75 Electronic computers. Computer science |
| Depositing User: | EAI Editor II. |
| Date Deposited: | 16 Sep 2020 08:38 |
| Last Modified: | 16 Sep 2020 08:38 |
| URI: | https://eprints.eudl.eu/id/eprint/313 |
Actions (login required)
 |
View Item |
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)
