Our algorithm focuses on Audio Music Mood Classification task. We propose two mid-level features which can catch the chord tension and roughness of the sound, which have crucial roles in making mood in the music. From the experiment with 132 exemplar songs which MIREX offers, we find that those two features increase the performance of the Audio Music Mood classification system.

We present a novel, flexible statistical approach for modelling music and text jointly. The approach is based on multi-modal mixture models and maximum a posteriori estimation using EM. The learned models can be used to browse databases with documents containing music and text, to search for music using queries consisting of music and text (lyrics and other contextual information), to annotate ...

We have so various types of entertainment, and music is one of the most popular one. In this paper, we proposed music recommendation system that interactively adapts a user’s personal affection with only a simple operation, in which both acoustic and meta features are used. The more a user uses the proposed system, the better the system adapts the user’s personal affection and recommends the su...

This project aims at developing a rich environment that integrates music in order to reinforce learning. Fostering learning through music is based on the visualization of concept maps. This novelty approach relates the rhythm and melody of a song with the dynamic appearance of the concept map; this is carry out by changing some design properties of the elements that composed the concept map. We...

The analysis of expressive performance, an important research topic in Computer Music, is almost exclusively devoted to the study of Western Classical piano music. Instruments like the acoustic guitar and styles like Bossa Nova and Samba have been little studied, despite their harmonic and rhythmic richness. This paper describes some experimental results obtained with the extraction of rhythmic...

We developed a music information retrieval system based on singing voice timbre, i.e., a system that can search for songs in a database that have similar vocal timbres. To achieve this, we developed a method for extracting feature vectors that represent characteristics of singing voices and calculating the vocal-timbre similarity between two songs by using a mutual information content of their ...

Genius is a popular commercial music recommender system that is based on collaborative filtering of huge amounts of user data. To understand the aspects of music similarity that collaborative filtering can capture, we compare Genius to two canonical music recommender systems: one based purely on artist similarity, the other purely on similarity of acoustic content. We evaluate this comparison w...

In this paper, we will examine the importance of music complexity as a factor for melody recognition in multi-voiced popular music. The assumption is that the melody (or lead instrument) will contain the largest amount of information – that it will be the least redundant voice. Measures of melodic complexity calculated from pitch and timing information are proposed. We test the different comple...

Musical genre classification is the automatic classification of audio signals into user defined labels describing pieces of music. A problem inherent to genre classification experiments in music information retrieval research is the use of songs from the same artist in both training and test sets. We show that this does not only lead to overoptimistic accuracy results but also selectively favou...

We study the impact of the presence of lyrics on music mood perception for both Canadian and Chinese listeners by conducting a user study of Canadians not of Chinese origin, Chinese-Canadians, and Chinese people who have lived in Canada for fewer than three years. While our original hypotheses were largely connected to cultural components of mood perception, we also analyzed how stable mood ass...