  Audio-visual speech enhancement (AV-SE) aims to enhance degraded speech along
with extra visual information such as lip videos, and has been shown to be more
effective than audio-only speech enhancement. This paper proposes further
incorporating ultrasound tongue images to improve lip-based AV-SE systems'
performance. Knowledge distillation is employed at the training stage to
address the challenge of acquiring ultrasound tongue images during inference,
enabling an audio-lip speech enhancement student model to learn from a
pre-trained audio-lip-tongue speech enhancement teacher model. Experimental
results demonstrate significant improvements in the quality and intelligibility
of the speech enhanced by the proposed method compared to the traditional
audio-lip speech enhancement baselines. Further analysis using phone error
rates (PER) of automatic speech recognition (ASR) shows that palatal and velar
consonants benefit most from the introduction of ultrasound tongue images.
