natural langauge processing
Even though intelligent systems such as Siri or Google Assistant are enjoyable (and useful) dialog partners, users can only access predefined functionality. Enabling end-users to extend the functionality of intelligent systems will be the next big thing. To promote research in this area we carried out an empirical study on how laypersons teach robots new functions by means of natural language instructions. The result is a labeled corpus consisting of 3168 submissions given by 870 subjects.
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The presented dataset has been used as a basis for CAO - a system for analysis of emoticons in Japanese online communication, developed by Ptaszynski et al. (2010). Emoticons are strings of symbols widely used in text-based online communication to convey user emotions. The database contains: 1) a predetermined raw emoticon database containing over ten thousand emoticon samples extracted from the Web, 2) emoticon parts automatically divided from raw emoticons into semantic areas representing “mouths” or “eyes”.
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