We have been conducting research to develop a music information retrieval system which retrieves music based on user preferences. In order to conduct evaluation experiments, it is necessary to accumulate an experiment set of music data, and collect user ratings of each music data included in this data set. Two music data sets were prepared for user evaluation: the RWC Popular Music Database, wh...

This paper describes a music browsing assistance service, Songrium (http://songrium.jp), which increases user enjoyment when listening to songs and allows visualization and exploration of a “Web of Music”. We define a Web of Music in this paper to be a network of “web-native music”, which we define in turn to be music that is published, shared, and remixed (has derivative works created) entirel...

Most existing studies on music mood classification have been focusing on Western music while little research has investigated whether mood categories, audio features, and classification models developed from Western music are applicable to non-Western music. This paper attempts to answer this question through a comparative study on English and Chinese songs. Specifically, a set of Chinese pop s...

Today, people listen to music on their mobile phone or other playback devices. Jukefox is a special music player running on Google’s smart phone operating system Android. It’s capable of recognizing similarities between multiple songs, albums and artists using data based on a huge music similarity map [1] which classifies songs into a high-dimensional space. Songs with small distance are simila...

The available evidence indicates that the music of a culture reflects the speech rhythm of the prevailing language. The normalized pairwise variability index (nPVI) is a measure of durational contrast between successive events that can be applied to vowels in speech and to notes in music. Music-language parallels may have implications for the acquisition of language and music, but it is unclear...

Familiarity is a crucial factor in music engagement, but very few study focuses on its neural correlates. We investigated effects of familiarity based on electroencephalogram in music-emotion recognition. Our research focused on self-reporting and continuous annotation based on the hypothesis that emotion in music experiencing is subjective and varies over time. Our methodology allowed subject ...

In this paper, we explore the classification of emotions in songs, using the music and the lyrics representation of the songs. We introduce a novel corpus of music and lyrics, consisting of 100 songs annotated for emotions. We show that textual and musical features can both be successfully used for emotion recognition in songs. Moreover, through comparative experiments, we show that the joint u...

Choices in music express our taste and personality. Different people have different collections of favorite songs. The explosive growth of digital media makes it easier to access any songs we want. Consequently, finding the songs best fit to our tastes becomes more challenging. Existing solutions record user patterns of listening to music, then make recommendation lists for users. By applying i...