63.6k citations · 65.7k across the 31 of their papers we have counts for
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On Using Backpropagation for Speech Texture Generation and Voice Conversion
Jan Chorowski, Ron J. Weiss, Rif A. Saurous +1
Inspired by recent work on neural network image generation which rely on backpropagation towards the network inputs, we present a proof-of-concept system for speech texture synthes…
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
Jonathan Shen, Ruoming Pang, Ron J. Weiss +10
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 predictio…
State-of-the-art Speech Recognition With Sequence-to-Sequence Models
Chung-Cheng Chiu, Tara N. Sainath, Yonghui Wu +11
Attention-based encoder-decoder architectures such as Listen, Attend, and Spell (LAS), subsume the acoustic, pronunciation and language model components of a traditional automatic…
Multilingual Speech Recognition With A Single End-To-End Model
Shubham Toshniwal, Tara N. Sainath, Ron J. Weiss +4
Training a conventional automatic speech recognition (ASR) system to support multiple languages is challenging because the sub-word unit, lexicon and word inventories are typically…
Tacotron: Towards End-to-End Speech Synthesis
Yuxuan Wang, RJ Skerry-Ryan, Daisy Stanton +11
A text-to-speech synthesis system typically consists of multiple stages, such as a text analysis frontend, an acoustic model and an audio synthesis module. Building these component…
Online and Linear-Time Attention by Enforcing Monotonic Alignments
Colin Raffel, Minh-Thang Luong, Peter J. Liu +2
Recurrent neural network models with an attention mechanism have proven to be extremely effective on a wide variety of sequence-to-sequence problems. However, the fact that soft at…