8th International Conference on Spoken Language Processing

Jeju Island, Korea
October 4-8, 2004

A Study on Model-Based Equal Error Rate Estimation for Automatic Speaker Verification

Hsiao-Chuan Wang, Jyh-Min Cheng

National Tsing Hua University, Taiwan

Usually, we need a large number of testing samples to evaluate the performance of automatic speaker verification (ASV) systems. The equal error rate (EER) is a common measure for this purpose. It is derived according to the threshold determined by finding the verification score when the false rejection rate (FRR) equals to the false acceptance rate (FAR). In this paper, a method of model-based EER estimation for the ASV system is proposed. The goal is to estimate the EER directly from the speaker model parameters without running the speaker verification experiments using a large number of testing samples. The verification scores are computed using the model parameters, and then both FRR and FAR are derived. With a small number of testing samples, we can adjust the score distribution to estimate the EER of the ASV system. The experimental result shows that the proposed method is effective and very promising for feedback loop design of an ASV system.

Full Paper

Bibliographic reference.  Wang, Hsiao-Chuan / Cheng, Jyh-Min (2004): "A study on model-based equal error rate estimation for automatic speaker verification", In INTERSPEECH-2004, 1793-1796.