Deepmind Technologies Limited

Yazhe Li

Oriol Vinyals

Aaron Gerard Antonius Van Den Oord

Thomas Chadwick Walters

Sze Chie Lim

Alejandro Luebs

Cristina Garbacea

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an encoder neural network that is configured to process an input observation to generate a latent representation of the input observation. In one aspect, a method includes: obtaining a sequence of observations; for each observation in the sequence of observations, processing the observation using the encoder neural network to generate a latent representation of the observation; for each of one or more given observations in the sequence of observations: generating a context latent representation of the given observation; and generating, from the context latent representation of the given observation, a respective estimate of the latent representations of one or more particular observations that are after the given observation in the sequence of observations.

Learning observation representations by predicting the future in latent space

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating discrete latent representations of input audio data. Only the discrete latent representation needs to be transmitted from an encoder system to a decoder system in order for the decoder system to be able to effectively to decode, i.e., reconstruct, the input audio data.

Speech coding using content latent embedding vectors and speaker latent embedding vectors

Growing community of inventors

London, United Kingdom

Yazhe Li