  A challenge in speech production research is to predict future tongue
movements based on a short period of past tongue movements. This study tackles
speaker-dependent tongue motion prediction problem in unlabeled ultrasound
videos with convolutional long short-term memory (ConvLSTM) networks. The model
has been tested on two different ultrasound corpora. ConvLSTM outperforms
3-dimensional convolutional neural network (3DCNN) in predicting the
9\textsuperscript{th} frames based on 8 preceding frames, and also demonstrates
good capacity to predict only the tongue contours in future frames. Further
tests reveal that ConvLSTM can also learn to predict tongue movements in more
distant frames beyond the immediately following frames. Our codes are available
at: https://github.com/shuiliwanwu/ConvLstm-ultrasound-videos.
