Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an audio signal from input text. In one aspect, a method comprises receiving a request to convert input text into an audio signal, wherein the input text comprises multiple tokenized text inputs, generating, using a first generative neural network, a semantic representation of the tokenized text inputs comprising semantic tokens representing semantic content of the tokenized text inputs, each semantic token being selected from a vocabulary of semantic tokens, generating, using a second generative neural network and conditioned on at least the semantic representation, an acoustic representation of the semantic representation comprising one or more respective acoustic tokens representing acoustic properties of the audio signal, and processing the acoustic representation using a decoder neural network to generate the audio signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a prediction of an audio signal. One of the methods includes receiving a request to generate an audio signal; obtaining a semantic representation of the audio signal; generating, using one or more generative neural networks and conditioned on at least the semantic representation, an acoustic representation of the audio signal; and processing at least the acoustic representation using a decoder neural network to generate the prediction of the audio signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a prediction of an audio signal. One of the methods includes receiving a request to generate an audio signal; obtaining a semantic representation of the audio signal; generating, using one or more generative neural networks and conditioned on at least the semantic representation, an acoustic representation of the audio signal; and processing at least the acoustic representation using a decoder neural network to generate the prediction of the audio signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a prediction of an audio signal. One of the methods includes receiving a request to generate an audio signal; obtaining a semantic representation of the audio signal; generating, using one or more generative neural networks and conditioned on at least the semantic representation, an acoustic representation of the audio signal; and processing at least the acoustic representation using a decoder neural network to generate the prediction of the audio signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing reinforcement learning with centralized inference and training One of the methods includes receiving, at a current time-step in a plurality of time-steps, a respective observation by an actor for each environment of a plurality of environments; obtaining, for each environment, a respective reward for the actor as a result of the actor performing a respective action at a previous time-step preceding the current time-step; processing, for each environment, the respective observation and respective reward through a policy model; providing, to the actor, the respective policy outputs for each of the plurality of environments; maintaining at a repository and for each environment, a respective sequence of tuples corresponding to the actor; determining that a maintained sequence meets a threshold condition; and in response, training the policy model on the maintained sequence.