8. The method of claim 1 further comprising a step of building an at least one background model.
1. A method for determining whether a speaker uttering a tested utterance belongs to a predetermined set comprising an at least one known speaker, wherein an at least one training utterance is available for each of the at least one known speaker, the method comprising: extracting an at least one first feature of each of the at least one training utterance; estimating an at least one model from the at least one first feature; storing the at least one model within a storage device; capturing a tested utterance by a capturing or logging unit; extracting a second feature group from an at least one frame of the tested utterance; fast-scoring a part of the second feature group against the at least one model, to obtain an at least one temporary model score; determining an at least one fast model score using the at least one temporary model score; selecting an at least one probable model associated with the at least one temporary model score which is higher than other temporary model scores; scoring the second feature group against the at least one probable model, to obtain an at least one intermediate score; determining an at least one model score using the at least one intermediate score; selecting an at least one maximal score from the at least one model score; and the speaker is determined to belong to the predetermined set, if the at least one maximal score exceeds a threshold.