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We present Deep Voice 3, a fully-convolutional attention-based neuraltext-to-speech (TTS) system. Deep Voice 3 matches state-of-the-art neuralspeech synthesis systems in naturalness while training ten times faster. Wescale Deep Voice 3 to data set sizes unprecedented for TTS, training on morethan eight hundred hours of audio from over two thousand speakers. In addition,we identify common error modes of attention-based speech synthesis networks,demonstrate how to mitigate them, and compare several different waveformsynthesis methods. We also describe how to scale inference to ten millionqueries per day on one single-GPU server.

Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning