A Generalised Normalisation Method for Speaker Verication

In a speaker veri¯cation system, a claimed speaker's score is computed to accept or reject the speaker claim. Most of the current methods compute the score as the ratio of the claimed speaker's and the impostors ' likelihood functions. Based on analysing false acceptance and false rejection errors obtained by using these methods, we pro-pose a generalised method to ¯nd better scores which can reduce both error types. Proposed scores are the ratios of the functions of the claimed speaker's and the impos-tors ' likelihood functions. Experiments performed on the ANDOSL and YOHO speech corpora show better results for the proposed method. 1