Research Article
Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting
Table 1
Comparison of the proposed algorithm to conventional algorithm in the utterance based speech segment detection test for various noise environments.
| | | Proposed | Sohn et al. [10] |
Ramírez et al. [14] | Górriz et al. [15] | Li et al. [17] | Fukuda et al. [18] | Environments | (%) | (%) | (%) | (%) | (%) | (%) | Noise | SNR |
| Babble | High | 92.5 | 89.5 | 92.3 | 93.9 | 85.4 | 90.1 | Low | 88.7 | 81.4 | 90.1 | 91.3 | 74.3 | 86.4 | Restaurant | High | 91.4 | 90.1 | 91.9 | 92.2 | 83.2 | 89.8 | Low | 88.5 | 82.4 | 88.4 | 89.2 | 70.0 | 84.5 | Exhibition hall | High | 95.8 | 92.0 | 94.0 | 94.0 | 90.7 | 94.4 | Low | 92.9 | 84.3 | 90.1 | 90.5 | 78.9 | 90.1 | Car | High | 95.9 | 91.5 | 94.5 | 94.5 | 87.5 | 94.1 | Low | 92.5 | 86.4 | 90.5 | 91.0 | 77.4 | 88.8 |
| Average | 92.3 | 87.2 | 91.5 | 92.1 | 80.9 | 89.8 |
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