184 citations · 285 across the 11 of their papers we have counts for
7 papers · 1 filter
Wave-Tacotron: Spectrogram-free end-to-end text-to-speech synthesis
Ron J. Weiss, RJ Skerry-Ryan, Eric Battenberg +2
We describe a sequence-to-sequence neural network which directly generates speech waveforms from text inputs. The architecture extends the Tacotron model by incorporating a normali…
Learning to Speak Fluently in a Foreign Language: Multilingual Speech Synthesis and Cross-Language Voice Cloning
Yu Zhang, Ron J. Weiss, Heiga Zen +6
We present a multispeaker, multilingual text-to-speech (TTS) synthesis model based on Tacotron that is able to produce high quality speech in multiple languages. Moreover, the mode…
Direct speech-to-speech translation with a sequence-to-sequence model
Ye Jia, Ron J. Weiss, Fadi Biadsy +4
We present an attention-based sequence-to-sequence neural network which can directly translate speech from one language into speech in another language, without relying on an inter…
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…
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…
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…