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This paper proposes the taboo words similarity browsing system which is able to assist the naming process. The proposed system in this paper analyzes new texts - new words or sentences - into phonemes, compares their similarities of pronunciations between new words and taboo words from various language cultural areas. The system supports the effective visualization interfaces in order to visualize...
The personalized music recommender supports the user-favorite songs stored in a huge music database. In order to predict only user-favorite songs, managing user preferences information and genre classification are necessary. In our study, a very short feature vector, obtained from low dimensional projection and already developed audio features, is used for music genre classification problem. We applied...
In our research, classification of music preference based on brain-wave is studied. We assume that there is a clear difference between brain-wave when hearing favorite music and it when hearing disgusting music, and we collect the brain-wave of human while hearing the music. And, there are two methods of collecting: one is separation of favorite/disgusting music clips, and the other is mixing of them...
This paper proposes an automatic music service, the MyMusicShuffler, which recommends music based on received brain signals. This service is focused on eliminating the unnecessary hand interactions in multi-tasking environments. By analyzing brainwave signals, the application can select music which effectively reflects the emotional responses of the user in real time. This paper explains the implementation...
This paper proposes a matching engine of a query-by-singing/humming (QbSH) system of which database is constructed from polyphonic recordings such as MP3 files. Use of the database makes the system more practical since it saves the trouble of gathering MIDI files. The pitch sequences transcribed from polyphonic recordings may have errors, and to reduce the influence of the errors, the matching engine...
It has become general that consumers freely create contents and spend them for themselves on Web services in Web 2.0 environments. This research introduces the personalized contents recommendation system that answers the recent propensity trends about the multimedia contents based on web environments. The proposed system mined the usage history patterns of the target user and the related users from...
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