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We investigate the automatic processing of child speech therapy sessionsusing ultrasound visual biofeedback, with a specific focus on complementingacoustic features with ultrasound images of the tongue for the tasks of speakerdiarization and time-alignment of target words. For speaker diarization, wepropose an ultrasound-based time-domain signal which we call estimated tongueactivity. For word-alignment, we augment an acoustic model with low-dimensionalrepresentations of ultrasound images of the tongue, learned by a convolutionalneural network. We conduct our experiments using the Ultrasuite repository ofultrasound and speech recordings for child speech therapy sessions. For bothtasks, we observe that systems augmented with ultrasound data outperformcorresponding systems using only the audio signal.

Ultrasound tongue imaging for diarization and alignment of child speech therapy sessions