Speaker verification with cohort normalized scoring

• US 5,675,704 A
• Filed: 04/26/1996
• Issued: 10/07/1997
• Est. Priority Date: 10/09/1992
• Status: Expired due to Term

• Current Assignee: Lucent Technologies, Inc. (Nokia Corporation)
• Original Assignee: Lucent Technologies, Inc. (Nokia Corporation)
• Inventors: Juang, Biing-Hwang, Soong, Frank Kao-Ping, Rosenberg, Aaron Edward, Lee, Chin-Hui
• Primary Examiner(s): MacDonald, Allen R.
• Assistant Examiner(s): Opsasnick, Michael N.
• Application Number:
  US08/638,401
• Time in Patent Office: 529 Days
• Field of Search: 395/2.55-2.59
• US Class Current: 704/246
• CPC Class Codes: G10L 15/142 Hidden Markov Models [HMMs]
• CPC Class Codes: G10L 17/00 Speaker identification or verification techniques
• CPC Class Codes: G10L 17/12 Score normalisation
• CPC Class Codes: H04M 15/00 Arrangements for metering, time-control or time indication ; Metering, charging or billing arrangements for voice wireline or wireless communications, e.g. VoIP
• CPC Class Codes: H04M 2201/40 using speech recognition speech recognition per se G10L15/00
• CPC Class Codes: H04M 3/382 using authorisation codes or passwords
• CPC Class Codes: H04M 3/42204 Arrangements at the exchange for service or number selection by voice at the terminal H04M1/27

Abstract

A facility is provided for allowing a caller to place a telephone call by merely uttering a label identifying a desired called destination and to charge the telephone call to a particular billing account by merely uttering a label identifying that account. Alternatively, the caller may place the call by dialing or uttering the telephone number of the called destination or by entering a speed dial code associated with that telephone number. The facility includes a speaker verification system which employs cohort normalized scoring. Cohort normalized scoring provides a dynamic threshold for the verification process making the process more robust to variation in training and verification utterences. Such variation may be caused by, e.g., changes in communication channel characteristics or speaker loudness level.

Claims

1. 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.

2. The method of claim 1 wherein the individual is prompted to provide the utterance.

3. The method of claim 2 wherein the utterance comprises a series of digits.

4. The method of claim 3 wherein the digits in the series are chosen at random.

5. The method of claim 1 wherein the utterance comprises a predetermined set of one or more words.

6. The method of claim 1 wherein the utterance provided by the individual is provided with use of a communication channel having a first response characteristic and wherein utterances used to train the hidden Markov models of the person whose identity is claimed are provided with use of a communication channel having a second response characteristic.

7. The method of claim 6 wherein the communication channel having a first response characteristic comprises a microphone having a first microphone response characteristic, and wherein the communication channel having a second response characteristic comprises a microphone having a second microphone response characteristic.

8. The method of claim 1 wherein the step of analyzing the signal comprises the step of segmenting the feature signals into groups of feature signals which substantially represent words of the utterance.

9. The method of claim 8 wherein the step of segmenting is performed using a speech recognition system.

10. The method of claim 1 wherein the first and other likelihood signals are formed based on Viterbi scoring.

11. The method of claim 1 wherein the impostor selection criterion comprises determining a measure of similarity between the one or more hidden Markov models of the person whose identity is claimed and one or more hidden Markov models of another person.

12. The method of claim 1 wherein the acoustic similarity criterion comprises determining a measure of acoustic similarity between the person whose identity is claimed and another person based on

a. a comparison of signals representing utterances spoken by the person whose identity is claimed and hidden Markov models of the other person;

and

b. a comparison of signals representing utterances spoken by the other person and hidden Markov models of the person whose identity is claimed.

13. The method of claim 1 wherein the step of forming a verification signal comprises the step of forming a signal reflecting a statistic of one or more other likelihood signals.

14. The method of claim 13 wherein the verification signal indicates that the individual is the person whose identity is claimed responsive to the first likelihood signal exceeding the statistic of the other likelihood signals.

15. The method of claim 13 wherein the first and other likelihood signals reflect log likelihood probabilities.

16. The method of claim 15 wherein the step of forming a verification signal further comprises the step of forming a signal reflecting a difference between the first likelihood signal and the signal reflecting a statistic of one or more other likelihood signals.

17. The method of claim 13 wherein the step of forming a verification signal further comprises the step of forming a signal reflecting a ratio of the first likelihood signal to the signal reflecting a statistic of one or more other likelihood signals.