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We investigate multi-speaker speech recognition from ultrasound images of thetongue and video images of the lips. We train our systems on imaging data frommodal speech, and evaluate on matched test sets of two speaking modes: silentand modal speech. We observe that silent speech recognition from imaging dataunderperforms compared to modal speech recognition, likely due to aspeaking-mode mismatch between training and testing. We improve silent speechrecognition performance using techniques that address the domain mismatch, suchas fMLLR and unsupervised model adaptation. We also analyse the properties ofsilent and modal speech in terms of utterance duration and the size of thearticulatory space. To estimate the articulatory space, we compute the convexhull of tongue splines, extracted from ultrasound tongue images. Overall, weobserve that the duration of silent speech is longer than that of modal speech,and that silent speech covers a smaller articulatory space than modal speech.Although these two properties are statistically significant across speakingmodes, they do not directly correlate with word error rates from speechrecognition.

Silent versus modal multi-speaker speech recognition from ultrasound and video