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Touch-Supported Voice Recording to Facilitate Forced Alignment of Text and Speech in an E-Reading Interface

Reading a book together with a family member who has impaired vision or other difficulties reading is an important social bonding activity. However, for the person being read to, there is little support in making these experiences repeatable. While audio can easily be recorded, synchronizing it with the text for later playback requires the use of forced alignment algorithms, which do not perform well on amateur read-aloud speech. We propose a human-in-the-loop approach to augmenting such algorithms, in the form of touch metaphors during collocated read-aloud sessions using tablet e-readers. The metaphor is implemented as a finger-follows-text tracker. We explore how this could better handle the variability of amateur reading, which poses accuracy challenges for existing forced alignment techniques. Data collected from users reading aloud as assisted by touch metaphors show increases in the accuracy of forced alignment algorithms and reveal opportunities for how to better support reading aloud.