The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

Deep generative models are a class of techniques that train deep neural networks to model
the distribution of training samples. Research has fragmented into various interconnected …

Abstract Language models have been successfully used to model natural signals, such as
images, speech, and music. A key component of these models is a high quality neural …

We introduce a state-of-the-art real-time, high-fidelity, audio codec leveraging neural
networks. It consists in a streaming encoder-decoder architecture with quantized latent …

We introduce AudioLM, a framework for high-quality audio generation with long-term
consistency. AudioLM maps the input audio to a sequence of discrete tokens and casts …

Generating sound effects that people want is an important topic. However, there are limited
studies in this area for sound generation. In this study, we investigate generating sound …

Despite recent progress in generative adversarial network (GAN)-based vocoders, where
the model generates raw waveform conditioned on acoustic features, it is challenging to …

We present SoundStream, a novel neural audio codec that can efficiently compress speech,
music and general audio at bitrates normally targeted by speech-tailored codecs …

Abstract The Video-to-Audio (V2A) model has recently gained attention for its practical
application in generating audio directly from silent videos, particularly in video/film …

Recently, denoising diffusion probabilistic models and generative score matching have
shown high potential in modelling complex data distributions while stochastic calculus has …