Name
Abstract | ||
|---|---|---|
This paper proposes a unified system for both visual speech recognition and speaker identification. The proposed system can handle image and depth data if they are available. The proposed system consists of four consecutive steps, namely, 3D face pose tracking, mouth region extraction, features computing, and classification using the Support Vector Machine method. The system is experimentally evaluated on three public datasets, namely, MIRACL-VC1, OuluVS, and CUAVE. In one hand, the visual speech recognition module achieves up to 96 % and 79.2 % for speaker dependent and speaker independent settings, respectively. On the other hand, speaker identification performs up to 98.9 % of recognition rate. Additionally, the obtained results demonstrate the importance of the depth data to resolve the subject dependency issue. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-25903-1_33 | ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, ACIVS 2015 |
Keywords | Field | DocType |
Mouth feature extraction,Biometry,Lip-reading,Speaker identification,Visual speech recognition | Mouth region,Speaker identification,Pose tracking,Pattern recognition,Computer science,Support vector machine,Speech recognition,Speaker recognition,Artificial intelligence,Speaker diarisation,Speech technology | Conference |
Volume | ISSN | Citations |
9386 | 0302-9743 | 5 |
PageRank | References | Authors |
0.53 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmed Rekik | 1 | 29 | 3.11 |
| Achraf Ben-Hamadou | 2 | 57 | 6.47 |
| Walid Mahdi | 3 | 116 | 25.49 |