Name
Title | ||
|---|---|---|
Noise robust voice activity detection using joint phase and magnitude based feature enhancement |
Abstract | ||
|---|---|---|
Recently, deep neural network (DNN)-based feature enhancement has been proposed for many speech applications. DNN-enhanced features have achieved higher performance than raw features. However, phase information is discarded during most conventional DNN training. In this paper, we propose a DNN-based joint phase- and magnitude -based feature (JPMF) enhancement (JPMF with DNN) and a noise-aware training (NAT)-DNN-based JPMF enhancement (JPMF with NAT-DNN) for noise-robust voice activity detection (VAD). Moreover, to improve the performance of the proposed feature enhancement, a combination of the scores of the proposed phase- and magnitude-based features is also applied. Specifically, mel-frequency cepstral coefficients (MFCCs) and the mel-frequency delta phase (MFDP) are used as magnitude and phase features. The experimental results show that the proposed feature enhancement significantly outperforms the conventional magnitude-based feature enhancement. The proposed JPMF with NAT-DNN method achieves the best relative equal error rate (EER), compared with individual magnitude- and phase-based DNN speech enhancement. Moreover, the combined score of the enhanced MFCC and MFDP using JPMF with NAT-DNN further improves the VAD performance. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s12652-017-0482-8 | Journal of Ambient Intelligence and Humanized Computing |
Keywords | Field | DocType |
Deep neural network (DNN), Phase information, Noise-robust VAD, Feature enhancement | Speech enhancement,Magnitude (mathematics),Mel-frequency cepstrum,Pattern recognition,Computer science,Voice activity detection,Word error rate,Speech applications,Speech recognition,Artificial intelligence,Artificial neural network,Machine learning | Journal |
Volume | Issue | ISSN |
8 | 6 | 1868-5145 |
Citations | PageRank | References |
1 | 0.37 | 24 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khomdet Phapatanaburi | 1 | 3 | 0.79 |
| Longbiao Wang | 2 | 272 | 44.38 |
| Zeyan Oo | 3 | 5 | 1.49 |
| Weifeng Li | 4 | 136 | 22.50 |
| Seiichi Nakagawa | 5 | 598 | 104.03 |
| Masahiro Iwahashi | 6 | 224 | 42.55 |