  As handwriting input becomes more prevalent, the large symbol inventory
required to support Chinese handwriting recognition poses unique challenges.
This paper describes how the Apple deep learning recognition system can
accurately handle up to 30,000 Chinese characters while running in real-time
across a range of mobile devices. To achieve acceptable accuracy, we paid
particular attention to data collection conditions, representativeness of
writing styles, and training regimen. We found that, with proper care, even
larger inventories are within reach. Our experiments show that accuracy only
degrades slowly as the inventory increases, as long as we use training data of
sufficient quality and in sufficient quantity.
