Michael A Lazarus

US Patent:

20200286485, Sep 10, 2020

Filed:

Sep 24, 2019

Appl. No.:

16/581566

Inventors:

- Costa Mesa CA, US
Wolf Kohn - Costa Mesa CA, US
Yanfang Shen - Costa Mesa CA, US
Cornelius Raths - Costa Mesa CA, US
Michael Lazarus - Costa Mesa CA, US
Peter Nguyen - Costa Mesa CA, US
Karl Schwamb - Mission Viejo CA, US

International Classification:

G10L 15/26
G10L 15/02
G10L 15/06

Abstract:

Methods and systems for transcribing a media file using a human intelligence task service and/or reinforcement learning are provided. The disclosed systems and methods provide opportunities for a segment of the input media file to be automatically re-analyzed, re-transcribed, and/or modified for re-transcription using a human intelligence task (HIT) service for verification and/or modification of the transcription results. The segment can also be reanalyzed, reconstructed, and re-transcribed using a reinforcement learning enabled transcription model.

US Patent:

20190385610, Dec 19, 2019

Filed:

Dec 10, 2018

Appl. No.:

16/215371

Inventors:

- Costa Mesa CA, US
Wolf Kohn - Costa Mesa CA, US
Yanfang Shen - Costa Mesa CA, US
Cornelius Raths - Costa Mesa CA, US
Michael Lazarus - Costa Mesa CA, US
Peter Nguyen - Costa Mesa CA, US

International Classification:

G10L 15/26
G06N 20/00
G10L 25/24
G10L 25/90
G10L 15/02
G10L 15/22

Abstract:

Methods and systems for transcribing a media file using reinforcement learning are provided. In one aspect, the method includes: identifying a low confidence of accuracy portion from a transcription result of the media file; constructing a phoneme sequence that includes an audio segment corresponding to the identified low confidence of accuracy portion, based on at least on a reward function; creating a new audio waveform based at least on the constructed phoneme sequence; and generating a new transcription using a transcription engine based on the new audio waveform.