184 citations · 285 across the 11 of their papers we have counts for
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cs.SD2020
Parallel Tacotron: Non-Autoregressive and Controllable TTS
Isaac Elias, Heiga Zen, Jonathan Shen +4
Although neural end-to-end text-to-speech models can synthesize highly natural speech, there is still room for improvements to its efficiency and naturalness. This paper proposes a…
cs.SD2019★ 23 cited
LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech
Heiga Zen, Viet Dang, Rob Clark +5
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, whi…
cs.SD2018
Synthesizing Diverse, High-Quality Audio Textures
Joseph Antognini, Matt Hoffman, Ron J. Weiss
Texture synthesis techniques based on matching the Gram matrix of feature activations in neural networks have achieved spectacular success in the image domain. In this paper we ext…