Abstract: Systems, methods, and apparatus for generating binaural audio waveform from mono waveform data. In an aspect, operations include generating, based on a mono waveform data and positional data, left signal data and right signal data, wherein the left signal data and the right signal data are initial estimates of perceived signals of the mono waveform based on the positional data; processing the left signal data and right signal data, based on the positional data, to generate amplitude scaled left signal data and amplitude scaled right signal data; and separately processing the amplitude scaled left signal data and the amplitude scaled right signal data by a denoising vocoder to generate left output signal data and right output signal data that together define a binaural audio waveform based on the mono waveform data.

Abstract: A method includes receiving an input sequence of speech features characterizing a spoken prompt. The method also includes generating a corresponding sequence of audio encodings using an audio encoder of a spoken language model. Without applying any intermediary cross-attention to the sequence of audio encoding between the audio encoder and a language model decoder of the spoken language model, the method includes processing the sequence of audio encodings generated by the audio encoder using the language model decoder to generate an output sequence of speech features characterizing a continuation of the spoken prompt.

Abstract: Training and/or utilizing a Speech-To-Speech Translation (S2ST) system that can be used to generate, based on processing source audio data that captures a spoken utterance in a source language, target audio data that includes a synthetic spoken utterance that is spoken in a target language and that corresponds, both linguistically and para-linguistically, to the spoken utterance in the source language. Implementations that are directed to training the S2ST system utilize an unsupervised approach, with monolingual speech data, in training the S2ST system.