Name
Abstract | ||
|---|---|---|
Automatic speaker verification systems can be spoofed through recorded, synthetic, or voice converted speech of target speakers. To make these systems practically viable, the detection of such attacks, referred to as presentation attacks, is of paramount interest. In that direction, this paper investigates two aspects: 1) a novel approach to detect presentation attacks where, unlike conventional a... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TASLP.2017.2743340 | IEEE/ACM Transactions on Audio, Speech, and Language Processing |
Keywords | Field | DocType |
Speech,Feature extraction,Speech processing,Databases,Mel frequency cepstral coefficient,Computational modeling | Speech processing,Mel-frequency cepstrum,Spoofing attack,Computer science,Artificial intelligence,Classifier (linguistics),Discriminative model,System software,Pattern recognition,Speech recognition,Feature extraction,Statistics,Microphone | Journal |
Volume | Issue | ISSN |
25 | 11 | 2329-9290 |
Citations | PageRank | References |
3 | 0.42 | 32 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hannah Muckenhirn | 1 | 29 | 3.08 |
| Pavel Korshunov | 2 | 240 | 23.24 |
| Mathew Magimai-Doss | 3 | 516 | 54.76 |
| Sébastien Marcel | 4 | 1984 | 123.84 |