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20182022
most citedStyle Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis

542 citations · 1.8k across the 25 of their papers we have counts for

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Showing 2018Show all

5 papers · 1 filter

cs.CL2018★ 14 cited

Leveraging Weakly Supervised Data to Improve End-to-End Speech-to-Text Translation

Ye Jia, Melvin Johnson, Wolfgang Macherey +6

End-to-end Speech Translation (ST) models have many potential advantages when compared to the cascade of Automatic Speech Recognition (ASR) and text Machine Translation (MT) models…

cs.CL2018★ 43 cited

Hierarchical Generative Modeling for Controllable Speech Synthesis

Wei-Ning Hsu, Yu Zhang, Ron J. Weiss +9

This paper proposes a neural sequence-to-sequence text-to-speech (TTS) model which can control latent attributes in the generated speech that are rarely annotated in the training d…

eess.AS2018★ 50 cited

VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking

Quan Wang, Hannah Muckenhirn, Kevin Wilson +7

In this paper, we present a novel system that separates the voice of a target speaker from multi-speaker signals, by making use of a reference signal from the target speaker. We ac…

cs.CL2018★ 431 cited

Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis

Ye Jia, Yu Zhang, Ron J. Weiss +8

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 d…

cs.CL2018★ 542 cited

Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis

Yuxuan Wang, Daisy Stanton, Yu Zhang +7

In this work, we propose "global style tokens" (GSTs), a bank of embeddings that are jointly trained within Tacotron, a state-of-the-art end-to-end speech synthesis system. The emb…