| Autor: |
Masoud Geravanchizadeh, Sina Ghalamiosgouei |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2020, Iss 1, Pp 1-15 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1687-4722 |
| DOI: |
10.1186/s13636-020-00188-y |
| Popis: |
Abstract In real applications, environmental effects such as additive noise and room reverberation lead to a mismatch between training and testing signals that substantially reduces the performance of far-field speaker identification. As a solution to this mismatch problem, in this paper, a new binaural speaker identification system is proposed which employs the well-known equalization-cancelation technique in its structure. The equalization-cancelation algorithm is employed to enhance the input test speech and alleviate the detrimental effects of noise and reverberation in the speaker identification system. The performance of the proposed speaker identification system is compared with unprocessed identification systems and a traditional binaural speaker identification system from the literature. The proposed system is evaluated in both anechoic and reverberant conditions using different types of noise at various azimuthal positions. Simulation results show the superiority of the proposed method in all experimental conditions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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