Speaker verification with cohort normalized scoring

A method of verifying a claim of identity made by an individual based on a signal representing an utterance provided by the individual, the method comprising the steps of:

• a. analyzing the signal representing the utterance to form a plurality of feature signals characterizing the utterance;
• b. forming a first likelihood signal, based on the plurality of feature signals and one or more hidden Markov models trained using utterances spoken by a person whose identity is claimed, the first likelihood signal reflecting a probability that the individual's utterance was spoken by the person whose identity is claimed;
• c. forming one or more other likelihood signals based on the plurality of feature signals and one or more hidden Markov models trained using utterances spoken by a set of one or more other speakers who are acoustically similar to the person whose identity is claimed, said one or more other speakers who are acoustically similar to the person whose identity is claimed having been selected from a universe of speakers based on an acoustic similarity criterion, the criterion based on the one or more hidden Markov models of the person whose identity is claimed, the universe of speakers including one or more speakers who are not acoustically similar to the person whose identity is claimed based on the acoustic similarity criterion, the other likelihood signals reflecting probabilities that the utterance was spoken by said one or more other speakers who are acoustically similar to the person whose identity is claimed;
• and
• d. forming a verification signal, based on the first likelihood signal and one or more of the other likelihood signals, and not based on hidden Markov models trained using utterances spoken by at least one of said one or more speakers who are not acoustically similar to the person whose identity is claimed, said verification signal indicating whether the individual is the person whose identity is claimed.