FAST, LANGUAGE-INDEPENDENT METHOD FOR USER AUTHENTICATION BY VOICE

• US 20140195237A1
• Filed: 01/09/2014
• Published: 07/10/2014
• Est. Priority Date: 03/16/2000
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: BELLEGARDA, Jerome R., SILVERMAN, Kim E. A.
• Granted Patent: US 9,218,809 B2
• Time in Patent Office: Days
• US Class Current: 704/249
• CPC Class Codes: G10L 15/07 to the speaker
• CPC Class Codes: G10L 17/04 Training, enrolment or model building
• CPC Class Codes: G10L 17/08 Use of distortion metrics or a particular distance between probe pattern and reference templates
• CPC Class Codes: G10L 17/14 Use of phonemic categorisation or speech recognition prior to speaker recognition or verification
• CPC Class Codes: G10L 17/22 Interactive procedures; Man-machine interfaces

Abstract

A method and system for training a user authentication by voice signal are described. In one embodiment, a set of feature vectors are decomposed into speaker-specific recognition units. The speaker-specific recognition units are used to compute distribution values to train the voice signal. In addition, spectral feature vectors are decomposed into speaker-specific characteristic units which are compared to the speaker-specific distribution values. If the speaker-specific characteristic units are within a threshold limit of the speaker-specific distribution values, the speech signal is authenticated.

Claims

1-32. -32. (canceled)

33. A method of speech-based user authentication, comprising:

at a device having one or more processors and memory;

receiving a plurality of different spoken utterances from a user;

for each of the plurality of different spoken utterances;

generating a respective phoneme-independent representation from the spoken utterance, the respective phoneme-independent representation including a respective spectral signature for each of a plurality of frames sampled from the spoken utterance; and

decomposing the respective phoneme-independent representation to obtain a content-independent recognition unit for the user;

calculating a content-independent recognition distribution value for the user based on the respective content-independent recognition units generated from the plurality of different spoken utterances; and

providing the content-independent recognition distribution value for use in a speaker authentication process.