Frederick W Weber

US Patent:

20200349957, Nov 5, 2020

Filed:

May 21, 2020

Appl. No.:

15/929795

Inventors:

- Seattle WA, US
Baiyang Liu - Bellevue WA, US
Frederick Victor Weber - New York NY, US

International Classification:

G10L 17/06
G10L 17/12
G10L 17/02
G10L 17/16
G10L 15/18
G10L 17/22

Abstract:

Features are disclosed for automatically identifying a speaker. Artifacts of automatic speech recognition (“ASR”) and/or other automatically determined information may be processed against individual user profiles or models. Scores may be determined reflecting the likelihood that individual users made an utterance. The scores can be based on, e.g., individual components of Gaussian mixture models (“GMMs”) that score best for frames of audio data of an utterance. A user associated with the highest likelihood score for a particular utterance can be identified as the speaker of the utterance. Information regarding the identified user can be provided to components of a spoken language processing system, separate applications, etc.

US Patent:

20190378517, Dec 12, 2019

Filed:

Jun 21, 2019

Appl. No.:

16/448788

Inventors:

- Seattle WA, US
Baiyang Liu - Bellevue WA, US
Frederick Victor Weber - New York NY, US

International Classification:

G10L 17/06
G10L 17/22
G10L 15/18
G10L 17/16
G10L 17/02
G10L 17/12

Abstract:

Features are disclosed for automatically identifying a speaker. Artifacts of automatic speech recognition (“ASR”) and/or other automatically determined information may be processed against individual user profiles or models. Scores may be determined reflecting the likelihood that individual users made an utterance. The scores can be based on, e.g., individual components of Gaussian mixture models (“GMMs”) that score best for frames of audio data of an utterance. A user associated with the highest likelihood score for a particular utterance can be identified as the speaker of the utterance. Information regarding the identified user can be provided to components of a spoken language processing system, separate applications, etc.

US Patent:

20170140761, May 18, 2017

Filed:

Jan 30, 2017

Appl. No.:

15/420018

Inventors:

- Seattle WA, US
Baiyang Liu - Bellevue WA, US
Frederick Victor Weber - New York NY, US

International Classification:

G10L 17/06
G10L 17/16
G10L 17/02
G10L 15/18
G10L 17/22

Abstract:

Features are disclosed for automatically identifying a speaker. Artifacts of automatic speech recognition (“ASR”) and/or other automatically determined information may be processed against individual user profiles or models. Scores may be determined reflecting the likelihood that individual users made an utterance. The scores can be based on, e.g., individual components of Gaussian mixture models (“GMMs”) that score best for frames of audio data of an utterance. A user associated with the highest likelihood score for a particular utterance can be identified as the speaker of the utterance. Information regarding the identified user can be provided to components of a spoken language processing system, separate applications, etc.