An information set-based robust text-independent speaker authentication
| Autor: | Hanmandlu Madasu, Jeevan Medikonda, Saurabh Bhardwaj |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Information set Computer science Speech recognition Speech corpus Computational intelligence 02 engineering and technology Speaker recognition VoxForge Theoretical Computer Science 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Entropy (information theory) 020201 artificial intelligence & image processing Geometry and Topology Mel-frequency cepstrum Software |
| Zdroj: | Soft Computing. 24:5271-5287 |
| ISSN: | 1433-7479 1432-7643 |
| Popis: | This paper presents a method for the extraction of twofold information set (TFIS) features for the text-independent speaker recognition. The method takes the Mel frequency cepstral coefficients from the frames of a sample speech signal and forms a matrix. From this, both spatial and temporal information components are derived based on the information set concept using the entropy framework. The TFIS features comprising their combination of two components are less in number thus reducing the computational time, complexity and improving the performance under the noisy environment. The proposed approach is tested on three datasets namely NIST-2003, VoxForge 2014 speech corpus and VCTK speech corpus in terms of speed, computational complexity, memory requirement and accuracy. Its performance is validated under different noisy environments at different signal-to-noise ratios. |
| Databáze: | OpenAIRE |
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