Abstract
Speaker verification systems require some kind of background model to reliably perform the verification task. Several algorithms have been proposed for the selection of cohort models to form a background model. This paper proposes a new cohort selection method called the Close Impostor Clustering (CIC). The new method is shown to outperform several other methods in a text-dependent verification task. Several normalization methods are also compared. With three cohort models and the best scorenormalization method, the CIC yielded an average Equal Error Rate (EER) of 0.8%, while the second best method (Maximally-Spread Close, MSC) yielded average EER of 1.1%.
| Original language | English |
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| Pages | 2977-2980 |
| Number of pages | 4 |
| State | Published - 1 Jan 2003 |
| Event | 8th European Conference on Speech Communication and Technology, EUROSPEECH 2003 - Geneva, Switzerland Duration: 1 Sep 2003 → 4 Sep 2003 |
Conference
| Conference | 8th European Conference on Speech Communication and Technology, EUROSPEECH 2003 |
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| Country/Territory | Switzerland |
| City | Geneva |
| Period | 1/09/03 → 4/09/03 |
ASJC Scopus subject areas
- Computer Science Applications
- Software
- Linguistics and Language
- Communication