Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting
new knowledge. By using DL, the extraction of advanced data representations and …

Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

In this work, we propose DiffWave, a versatile diffusion probabilistic model for conditional
and unconditional waveform generation. The model is non-autoregressive, and converts the …

This paper introduces WaveGrad, a conditional model for waveform generation which
estimates gradients of the data density. The model is built on prior work on score matching …

We introduce Jukebox, a model that generates music with singing in the raw audio domain.
We tackle the long context of raw audio using a multiscale VQ-VAE to compress it to discrete …

This explainer document aims to provide an overview of the current state of the rapidly
expanding work on synthetic data technologies, with a particular focus on privacy. The …

This paper introduces a new speech corpus called" LibriTTS" designed for text-to-speech
use. It is derived from the original audio and text materials of the LibriSpeech corpus, which …

Although end-to-end neural text-to-speech (TTS) methods (such as Tacotron2) are proposed
and achieve state-of-theart performance, they still suffer from two problems: 1) low efficiency …

This paper describes Tacotron 2, a neural network architecture for speech synthesis directly
from text. The system is composed of a recurrent sequence-to-sequence feature prediction …

We describe a neural network-based system for text-to-speech (TTS) synthesis that is able to
generate speech audio in the voice of many different speakers, including those unseen …