Google's DeepMind claims major milestone in making machines talk like humans ZDNet

On a scale from 1 to 5, WaveNet's quality of voice outstrips Google's current best parametric and concatenative systems. Google's UK artificial intelligence lab, DeepMind, has developed a deep neural network that produces more human-like speech than Google's previous text-to-speech (TTS) systems. DeepMind has published a new paper describing WaveNet, a convolutional neural network it says has closed the gap between machine-generated and human speech by 50 percent in both US English and Mandarin Chinese. Not only this, but the network can also seamlessly switch between different voices and generate realistic music fragments. The researchers note that today's best TTS systems, generally considered to be powered by Google, are built on "speech fragments" recorded from a single speaker.