VOICE AUTHENTICATION AND SPEECH RECOGNITION SYSTEM AND METHOD

• US 20160372116A1
• Filed: 08/22/2016
• Published: 12/22/2016
• Est. Priority Date: 01/24/2012
• Status: Active Application

• Current Assignee: Auraya Pty Limited
• Original Assignee: Auraya Pty Limited
• Inventors: SUMMERFIELD, Clive David
• Application Number:
  US15/243,906
• Publication Number:
  US 20160372116A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G10L 15/063 Training
• CPC Class Codes: G10L 15/07 to the speaker
• CPC Class Codes: G10L 17/00 Speaker identification or verification techniques
• CPC Class Codes: G10L 25/63 for estimating an emotional state

Abstract

A method for configuring a speech recognition system comprises obtaining a speech sample utilised by a voice authentication system in a voice authentication process. The speech sample is processed to generate acoustic models for units of speech associated with the speech sample. The acoustic models are stored for subsequent use by the speech recognition system as part of a speech recognition process.

Claims

1. A method for configuring a speech recognition system, the method comprising:

identifying a user;

selecting a training speech sample provided by the user, the training speech sample being associated with an emotional state of the user;

processing a selected unit of speech from the training speech sample to generate a corresponding acoustic model;

training a personalised acoustic model associated with the determined emotional state using the generated acoustic model, the personalised acoustic model being stored in an acoustic model store specific to the user;

accessing the personalised acoustic model store to determine an emotional state of the user during a subsequent speech recognition process.

2. A method in accordance with claim 1, wherein the personalised acoustic model is initially derived from a seed model.

3. A method in accordance with claim 1, further comprising implementing an authentication process for identifying the user, the authentication process being implemented by an authentication system.

4. A method in accordance with claim 3, wherein the training speech sample is provided by the user either during enrolment with the authentication system or during a subsequent authentication process carried out by the authentication system.

5. A method in accordance with claim 3, wherein the training speech sample is provided by the user during a speech recognition process that is implemented by the speech recognition system once the user has been authenticated.

6. A method in accordance with claim 1, wherein the subsequent speech recognition process comprises:

generating an acoustic model for a unit of speech derived from a speech sample uttered by the user during the subsequent speech recognition process;

comparing the acoustic model against one or more models stored in the personalised acoustic model store to generate respective comparison scores representative of how closely matched the models are; and

determining one or more emotional state(s) of the user based on the resultant scores.

7. A method in accordance with claim 6, wherein an emotional state is positively determined where the comparison score for the associated model meets or exceeds a predefined threshold.

8. A method in accordance with claim 1, further comprising accessing a personalised grammar model store associated with the user and training one or more grammar models associated with the determined emotional state using phonemes or words from the training speech sample

9. A method in accordance with claim 8, wherein the grammar models are evaluated in addition to the personalised acoustic models for determining the emotional state of the user during the subsequent speech recognition process.

10. A method according to claim 1, further comprising updating the personalised acoustic model store based on acoustic models generated from further processed speech samples uttered by the user.

11. A method in accordance with claim 10, further comprising determining a quality measure for each of the acoustic models stored in the personalised acoustic model store and continuing to update the acoustic modules until the quality measure reaches a predefined threshold.

12. A computer readable medium implementing a computer program comprising one or more instructions for controlling a computer system to implement a method in accordance with claim 1.

13. A method for configuring a speech recognition system, the method comprising:

identifying a user;

selecting a training speech sample provided by the user, the training speech sample being associated with an emotional state of the user;

processing the training speech sample to determine one or more phonemes or words therein;

training a personalised grammar model associated with the determined emotional state utilising the determined phonemes or words, the personalised grammar model being stored in a model store specific to the user;

accessing the personalised grammar model store to determine an emotional state of the user during a subsequent speech recognition process.