An Image-To-Speech iPad App
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Zhu, Xiaojin
Rosin, Jake
Jun, Kwang-Sung
Dyer, Charles R.
Maynord, Michael
Tiachunpun, Jitrapon
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Technical Report
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University of Wisconsin-Madison Department of Computer Sciences
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Abstract
We describe an iPad app which assists in language acquisition and development. Such an application can be used by clinicians for human developmental disabilities. A user drags images around on the screen. The app generates and speaks random (but sensible) phrases that matches the image interact. For example, if a user drags an image of a squirrel onto an image of a tree, the app may say "the squirrel ran up the tree." A key challenge is the automated creation of "sensible" English phrases, which we solve by using a large corpus and machine learning.
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TR1774