A method of deducing the user’s state of mind by analyzing pictographic characters and emoticons in mobile phone emails and a method of selecting music suitable for the user’s state of mind

As the ubiquitous environment is taking root, there are calls for services that deliver content appropriate for the individual userpsilas personal interests and preferences. Services are already being provided that deduce the interests or preferences of the user by analyzing his or her log data and provide content appropriate for his or her physical/mental/emotional state. A method of deducing the state of mind of the user has been proposed, which analyzes pictographic characters in emails sent by mobile phones. In this paper, we attempt to improve the accuracy of state-of-mind deduction by analyzing not only pictographic characters but also emoticons that many people use to express their feelings explicitly. We have developed an algorithm for extracting state-of-mind elements associated with each pictographic character or emoticon, and defining it with vector values of these elements. We have developed a prototype system, and verified the effectiveness of the algorithm by having a group of students use the system. We have applied the algorithm to the selection of music, which is considered to be close related to peoplepsilas feelings. Specifically, we have proposed a method of selecting an appropriate piece of music based on a music type, which is represented by the ldquonumber of chordsrdquo, ldquosound strengthrdquo, and ldquomelody patternrdquo in a piece of music. We have evaluated a music delivery service, which delivers a piece of music suitable for the current feeling of the user.