397 citations · 1.7k across the 82 of their papers we have counts for
5 papers · 1 filter
Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning
Wei Ping, Kainan Peng, Andrew Gibiansky +5
We present Deep Voice 3, a fully-convolutional attention-based neural text-to-speech (TTS) system. Deep Voice 3 matches state-of-the-art neural speech synthesis systems in naturaln…
Low-complexity implementation of convex optimization-based phase retrieval
Sercan O. Arik, Joseph M. Kahn
Phase retrieval has important applications in optical imaging, communications and sensing. Lifting the dimensionality of the problem allows phase retrieval to be approximated as a…
Deep Voice 2: Multi-Speaker Neural Text-to-Speech
Sercan Arik, Gregory Diamos, Andrew Gibiansky +5
We introduce a technique for augmenting neural text-to-speech (TTS) with lowdimensional trainable speaker embeddings to generate different voices from a single model. As a starting…
Deep Voice: Real-time Neural Text-to-Speech
Sercan O. Arik, Mike Chrzanowski, Adam Coates +9
We present Deep Voice, a production-quality text-to-speech system constructed entirely from deep neural networks. Deep Voice lays the groundwork for truly end-to-end neural speech…
Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting
Sercan O. Arik, Markus Kliegl, Rewon Child +5
Keyword spotting (KWS) constitutes a major component of human-technology interfaces. Maximizing the detection accuracy at a low false alarm (FA) rate, while minimizing the footprin…