| Autor: |
Thanh Thi Hien Duong, Phuong Cong Nguyen, Cuong Quoc Nguyen |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
EAI Endorsed Transactions on Context-aware Systems and Applications, Vol 4, Iss 13, Pp 1-8 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2409-0026 |
| DOI: |
10.4108/eai.14-3-2018.154342 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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