IP Library Granted Patent US 9,384,735
Granted Patent B2
US 9,384,735 · App. 14/341,054 · Granted Jul 5, 2016

Corrective feedback loop for automated speech recognition

Inventors: Marc White (Charlotte, NC); Igor Roditis Jablokov (Charlotte, NC); Victor Roman Jablokov (Charlotte, NC)
Assignee: Amazon Technologies, Inc.
G10L15/26G06F3/0236G10L15/22G10L15/30G10L15/183G10L15/19G10L2015/0631
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Quick Facts
Patent No.
US 9,384,735
App. No.
14/341,054
Granted
Jul 5, 2016
Kind
B2
Abstract

A method for facilitating the updating of a language model includes receiving, at a client device, via a microphone, an audio message corresponding to speech of a user; communicating the audio message to a first remote server; receiving, that the client device, a result, transcribed at the first remote server using an automatic speech recognition system (“ASR”), from the audio message; receiving, at the client device from the user, an affirmation of the result; storing, at the client device, the result in association with an identifier corresponding to the audio message; and communicating, to a second remote server, the stored result together with the identifier.

Claims (48)

1. A system comprising:

a computing device in communication with an electronic data store, the computing device configured to:

obtain audio data comprising speech from a client device;

receive an identifier of an application from the client device, wherein the application is associated with an initial language model;

generate a transcription of the speech using the initial language model;

transmit the transcription to the client device for presentation to a user;

receive feedback on the transcription from the client device; and

based at least in part on the feedback, generate an updated language model, wherein the electronic data store is configured to store at least one of the initial language model and the updated language model.

2. The system of claim 1 , wherein the feedback comprises at least one of an affirmation of the transcription, a disapproval of the transcription, or a correction to the transcription.

3. The system of claim 1 , wherein the computing device is further configured to generate one or more alternate transcriptions of the speech using the initial language model.

4. The system of claim 2 , wherein the computing device is further configured to transmit the one or more alternate transcriptions to the client device.

5. The system of claim 4 , wherein the feedback comprises a selection of an alternate transcription.

6. The system of claim 4 , wherein the one or more alternate transcriptions each have a transcription confidence value that satisfies a threshold.

7. The system of claim 1 , wherein the electronic data store is further configured to store one or more algorithms that, when executed, implement an automatic speech recognition engine.

8. A non-transitory computer-readable medium having stored thereon a computer-executable component configured to execute in one or more processors of a computing device, the computer-executable component being further configured to:

receive first audio data comprising first speech;

transcribe the first speech using a first language model to generate a first transcription;

provide the first transcription to a first client device;

receive feedback on the first transcription from the first client device;

based at least in part on the feedback on the first transcription, update the first language model;

select a second language model; and

based at least in part on the feedback on the transcription, update the second language model, wherein the second language model is not used to generate the first transcription.

9. The non-transitory computer-readable medium of claim 8 , wherein:

the first audio data comprising speech is associated with a user of the first client device; and

the first language model is associated with the user of the first client device.

10. The non-transitory computer-readable medium of claim 8 , wherein the computer-executable component is further configured to:

receive second audio data comprising second speech; and

transcribe the second speech with the updated first language model to generate a second transcription.

11. The non-transitory computer-readable medium of claim 8 , wherein the first audio data comprising first speech is received from the first client device.

12. The non-transitory computer-readable medium of claim 8 , wherein the first audio data comprising first speech is received from a second client device.

13. The non-transitory computer-readable medium of claim 8 , wherein the feedback comprises at least one of an affirmation of the first transcription, a disapproval of the first transcription, or a correction to the first transcription.

14. A computer-implemented method comprising:

under control of one or more computing devices configured with specific computer-executable instructions,

receiving audio data comprising speech from a first client device;

receiving an identifier of an application from the first client device, wherein a first language model is associated with the application

generating speech recognition results from the speech using the first language model;

providing the speech recognition results to the first client device;

receiving feedback on the speech recognition results from the first client device; and

updating the first language model based at least in part on the feedback.

15. The computer-implemented method of claim 14 , wherein the audio data is received from a second client device.

16. The computer-implemented method of claim 14 , wherein the speech recognition results comprise a transcription of the speech.

17. The computer-implemented method of claim 16 , wherein the feedback relates to at least one of a letter of the transcription, a syllable of the transcription, a word of the transcription, a phrase of the transcription, or a sentence of the transcription.

18. The computer-implemented method of claim 16 , further comprising:

generating a transcription identifier associated with the transcription;

transmitting the identifier to the first client device with the transcription; and

receiving the identifier from the first client device with the feedback on the speech recognition results.

19. The computer-implemented method of claim 14 , further comprising generating one or more alternative speech recognition results using the first language model.

20. The computer-implemented method of claim 19 , further comprising providing to the first client device an alternative speech recognition result from the one or more alternative speech recognition results with a confidence value that satisfies a threshold.

Assignments (2)
MERGER AND CHANGE OF NAME Recorded Apr 6, 2016
From: YAP, INC.; YAP LLC
To: YAP LLC
Reel/Frame 038210/0171 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 10, 2015
From: CANYON IP HOLDINGS LLC
To: AMAZON TECHNOLOGIES, INC.
Reel/Frame 037083/0914 →
Continuity (5)
Continuation 13621189 · Sep 15, 2012
Continuation 12407502 · Mar 19, 2009
Provisional Application 61038048 · Mar 19, 2008
Provisional Application 61041219 · Mar 31, 2008
Related Publication 20150025884A1 · Jan 22, 2015