Bandwidth extension of incoming data using neural networks

A system comprising one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to perform operations for improving communication quality on a data communications network, the operations comprising:

• receiving, at a communications node of the data communications network, an encoded input signal representing an input;
• decoding, at the communications node of the data communications network, the encoded input signal using a decoder of a codec to generate a low-resolution version of the input, the low-resolution version of the input comprising a first number of samples at a first sample rate over a first time period;
• and
• generating, from the low-resolution version of the input generated by decoding the encoded input signal, a high-resolution version of the input comprising a second, larger number of samples at a second, higher sample rate over the first time period, the generating comprising:
• generating, from the low-resolution version of the input generated by decoding the input signal, a conditioning input;
• and
• processing the conditioning input generated from the low-resolution version of the input using a generative neural network to generate the high-resolution version of the input.

One or more non-transitory computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations for improving communication quality on a data communications network, the operations comprising:

• receiving, at a communications node of the data communications network, an encoded input signal representing an input;
• decoding, at the communications node of the data communications network, the encoded input signal using a decoder of a codec to generate a low-resolution version of the input, the low-resolution version of the input comprising a first number of samples at a first sample rate over a first time period;
• and
• generating, from the low-resolution version of the input generated by decoding the encoded input signal, a high-resolution version of the input comprising a second, larger number of samples at a second, higher sample rate over the first time period, the generating comprising:
• generating, from the low-resolution version of the input generated by decoding the input signal, a conditioning input;
• and
• processing the conditioning input generated from the low-resolution version of the input using a generative neural network to generate the high-resolution version of the input.