The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 13, 2018

Filed:

May. 03, 2017
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Krishna Kamath Koteshwara, Santa Clara, CA (US);

Trausti Thor Kristjansson, San Jose, CA (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 21/02 (2013.01); G10L 19/005 (2013.01); G10L 15/22 (2006.01); G10L 25/30 (2013.01); G10L 15/06 (2013.01); G11B 27/038 (2006.01); G10L 21/0364 (2013.01); G10L 21/0332 (2013.01);
U.S. Cl.
CPC ...
G10L 21/0205 (2013.01); G10L 15/063 (2013.01); G10L 15/22 (2013.01); G10L 19/005 (2013.01); G10L 21/0332 (2013.01); G10L 21/0364 (2013.01); G10L 25/30 (2013.01); G11B 27/038 (2013.01); G10L 2015/223 (2013.01);
Abstract

A system configured to reconstruct audio signals. The system may identify missing audio samples due to packet loss or detect distortion caused by audio clipping and may reconstruct the audio data. The system may employ a forward-looking neural network that recursively predicts audio samples based on previous audio samples and/or a backward-looking neural network that recursively predicts audio samples based on subsequent audio samples. The system may generate audio data using only the forward-looking neural network for low latency applications or may generate audio data using both neural networks for mid to high latency applications. To reduce distortion in output audio data, the system may generate the audio data by cross-fading between outputs of the neural networks and/or may cross-fade between the generated audio data and the input audio data.


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