We analyze a dataset providing the complete information on the effective plays of thousands of music listeners during several months. Our analysis confirms a number of properties previously highlighted by research based on interviews and questionnaires, but also uncover new statistical patterns, both at the individual and collective levels. In particular, we show that individuals follow common ...

The emergence of the Internet as today’s primary medium of music distribution has brought about demands for fast and reliable ways to organize, access, and discover music online. To date, many applications designed to perform such tasks have risen to popularity; each relies on a specific form of music metadata to help consumers discover songs and artists that appeal to their tastes. Very few of...

In the continuing investigation of understanding the connection between music information retrieval (MIR) and the economics of music this paper focuses on mining economically viable song attributes. Identical features and attributes found in songs in one genre or place in time can have completely inverse translations as to the economic viability of a song. Partial cognates are pairs of features...

Searching and organizing growing digital music collections requires automatic classification of music. This paper describes a new system, tested on the task of artist identification, that uses support vector machines to classify songs based on features calculated over their entire lengths. Since support vector machines are exemplarbased classifiers, training on and classifying entire songs inst...

Automatic extraction of information from music data is an important and challenging issue in the field of content-based music retrieval. As part of the research effort, this study presents a technique that automatically identifies cover versions of songs specified by users. The technique enables users to search for songs with an identical tune, but performed by different singers, in different l...

Selecting the ‘right’ songs and putting them in the ‘right’ order are key to a great music listening or dance experience. ‘SatisFly’ is an interactive playlist generation system in which the user can tell what kind of songs should be contained in what order in the playlist, while she navigates through the music collection. The system uses constraint satisfaction to generate a playlist that meet...

Music is a powerful medium capable of eliciting a broad range of emotions. Although the relationship between language and music is well documented, relatively little is known about the effects of lyrics and the voice on the emotional processing of music and on listeners' preferences. In the present study, we investigated the effects of vocals in music on participants' perceived valence and arou...

Collections of electronic music are mostly organized according to playlists based on artist names and song titles. Music genres are inherently ambiguous and, to make matters worse, assigned manually by a diverse user community. People tend to organize music based on similarity to other music and based on the music’s emotional qualities. Taking this into account, we have designed a music player ...

In this work we propose a method to identify the raga of a Carnatic music signal. Raga is analogous to melody in Western music but is much richer and stronger in its representation. The main motive behind Raga identification is that it can be used as a good basis for music information retrieval of Carnatic music songs or Film songs based on Carnatic music. The input polyphonic music signal is a...

We evaluate the music taste representation computation and song matching capabilities of Jukefox, a smart music player for Android developed at the distributed computing group at ETH Zürich. We then use this music taste representation for single persons to create group playlists. A group playlist contains the aggregated songs of all group members, ordered from best to worst. The more group memb...