A research team at the National Institute of Informatics (NII/Tokyo, Japan) including Xin Wang, Shinji Takaki and Junichi Yamagishi has developed a neural source-filter (NSF) model for high-speed, high-quality voice synthesis. This technique, which combines recent deep-learning algorithms and a classical speech production model dated back to the 1960s, is capable not only of generating high-quality voice waveforms closely resembling the human voice, but also of conducting stable learning via neural networks.