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US 10,482,887 B1Granted
Machine learning model assisted enhancement of audio and/or visual communications
AssigneeAmazon Technologies, Inc.
InventorsMadhav Jha, Edo Liberty
Life of this patent
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Abstract
Techniques for using machine learning models to approximate a user in a communication are described. For example, a method of initiating a communication link with an edge device to exchange audio data; receiving a compressed audio data from the edge device; re-encoding the received compressed audio data using a re-encoding machine learning model to approximate a voice; and outputting the approximated voice is detailed.
Claims20
A computer-implemented method comprising:
- initiating a communication link between a first and a second edge device for the first and seconds edge devices to transmit and receive at least compressed audio data;
- determining a bandwidth of the communication link, the determined bandwidth to be used to set an amount of compression of audio data to be performed by the first edge device;
- transmitting a re-encoding machine learning model corresponding to a voice of a user of the first edge device to the second edge device, the second edge device to utilize the re-encoding machine learning model of the user of the first edge device to re-encoding at least the compressed audio data transmitted over the initiated communication link to approximate the voice of the user of the first edge device;
- and
- passing compressed audio data from the first edge device to the second edge device using the initiated communication link.
2 more elements
A computer-implemented method comprising:
- initiating a communication link with an edge device to exchange audio data;
- receiving a compressed audio data from the edge device;
- re-encoding the received compressed audio data using a re-encoding machine learning model to approximate a voice;
- and
- outputting the approximated voice.
2 more elements
A system comprising:
- a web services provider server to initiation communications between a first and a second edge device;
- and
- the first edge device including hardware execution resources to execute instructions stored in memory, the instructions upon execution to cause:
- a receipt of a compressed audio data from the second edge device,
- a re-encode of the received compressed audio data using a re-encoding machine learning model to approximate a voice;
- and
- a generation of the approximated voice.
4 more elements
Dependencies are inferred from the claim text.