Nowadays speech synthesis or text to speech (TTS), an ability of system to produce human
like natural sounding voice from the written text, is gaining popularity in the field of speech …

Speech synthesis, also known as text-to-speech (TTS), has attracted increasingly more
attention. Recent advances on speech synthesis are overwhelmingly contributed by deep …

Data center clusters that run DNN training jobs are inherently heterogeneous. They have
GPUs and CPUs for computation and network bandwidth for distributed training. However …

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 …

In this paper we propose WaveGlow: a flow-based network capable of generating high
quality speech from mel-spectrograms. WaveGlow combines insights from Glow [1] and …

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 …

Sequential models achieve state-of-the-art results in audio, visual and textual domains with
respect to both estimating the data distribution and generating desired samples. Efficient …

Voice cloning is a highly desired feature for personalized speech interfaces. We introduce a
neural voice cloning system that learns to synthesize a person's voice from only a few audio …

Current text-to-speech algorithms produce realistic fakes of human voices, making deepfake
detection a much-needed area of research. While researchers have presented various …

There is plenty of theoretical and empirical evidence that depth of neural networks is a
crucial ingredient for their success. However, network training becomes more difficult with …