Qualcomm Incorporated

Guillaume Konrad Sautière

Yang Yang

Vivek Rajendran

Daniel Jared Sinder

Taco Sebastiaan Cohen

Jongha Ryu

Zisis Iason Skordilis

A device includes one or more processors configured to generate, at an encoder portion of an autoencoder, first output data at least partially based on first input data and to generate, at a decoder portion or the autoencoder, a representation of the first input data at least partially based on the first output data. The one or more processors are configured to generate, at the encoder portion, second output data based on second input data and first state data and to generate, at the decoder portion, a representation of the second input data based on the second output data and second state data. Each of the first state data and the second state data correspond to the state of the decoder portion resulting from generation of the representation of the first input data. The first and second input data correspond to sequential values of a signal to be encoded.

Method and apparatus for recurrent auto-encoding

Techniques are described for coding audio signals. For example, using a neural network, a residual signal is generated for a sample of an audio signal based on inputs to the neural network. The residual signal is configured to excite a long-term prediction filter and/or a short-term prediction filter. Using the long-term prediction filter and/or the short-term prediction filter, a sample of a reconstructed audio signal is determined. The sample of the reconstructed audio signal is determined based on the residual signal generated using the neural network for the sample of the audio signal.

Artificial intelligence based audio coding

Growing community of inventors

Amsterdam, Netherlands

Guillaume Konrad Sautière