Name
Abstract | ||
|---|---|---|
One of the key issues in practical speech recognition is to achieve robust gender identification. Most conventional gender identification approaches use relevant features derived from the magnitude spectrum. In this paper, we propose a novel gender identification method using a group delay function (GDF). Based on the statistical analysis of the GDF, it is found that the GDF is an effective feature for gender identification. The experimental results demonstrate that the proposed method gives significant improvement compared to conventional methods. |
Year | Venue | Keywords |
|---|---|---|
2008 | INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5 | Gender Identification, Group Delay, GMM |
Field | DocType | Citations |
Phase spectrum,Pattern recognition,Computer science,Group delay and phase delay,Speech recognition,Artificial intelligence,Statistical analysis | Conference | 0 |
PageRank | References | Authors |
0.34 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kye-hwan Lee | 1 | 19 | 2.92 |
| Sang-Ick Kang | 2 | 25 | 4.81 |
| Jihyun Song | 3 | 15 | 4.36 |
| Joon-Hyuk Chang | 4 | 263 | 21.87 |