This paper presents SongExplorer, a system for the exploration of large music collections on tabletop interfaces. SongExplorer addresses the problem of finding new interesting songs on large music databases, from an interaction design perspective. Using high level descriptors of musical songs, SongExplorer creates a coherent 2D map based on similarity, in which neighboring songs tend to be more...

This study investigated the (mis)matching between tones and tunes in Cantonese songs in traditional operas and popular music, with a focus on composition processes. We calculated the degree of matching by tracking directions of pitch changes in consecutive syllables in the melody and lyrics, and also measured the musical range in absolute pitches. We then compared patterns discovered across gen...

This paper proposes a system that automatically locates and extracts songs from digitized movies and classifies the extracted songs according to their genre using a video-based genre identification algorithm. A song grammar particularly applicable to Bollywood movies has been proposed and used subsequently to construct a probabilistic timed automaton that differentiates songs from rest of the s...

The paper discusses some aspects of a work in progress aimed at the development of technologies for digitization of Bulgarian folk music and building a digital library with Bulgarian folk songs presented with their music, texts and notes. This library provides digital preservation of the sound recordings, lyrics and notations of more than 1000 Bulgarian folk songs and tools for various types of...

The “bag of frames” approach (BOF) to audio pattern recognition models signals as the long-term statistical distribution of their local spectral features, a prototypical implementation of which being Gaussian Mixture Models of Mel-Frequency Cepstrum Coefficients. This approach is the most predominent paradigm to extract high-level descriptions from music signals, such as their instrument, genre...

music analysis, information retrieval, multimedia indexing We motivate the problem of music recommendation based solely on acoustics from groups of related songs or 'song sets'. We propose four solutions which can be used with any acoustic-based similarity measure. The first builds a model for each song set and recommends new songs according to their distance from this model. The next three app...

OBJECTIVES Those exposed to more degrading sexual references in popular music are more likely to initiate intercourse at a younger age. The purpose of this study was to perform a content analysis of contemporary popular music with particular attention paid to the prevalence of degrading and non-degrading sexual references. We also aimed to determine if sexual references of each subtype were ass...

Music information retrieval has emerged as a mainstream research area in the past two decades. Experiments on music mood classification have been performed mainly on Western music based on audio, lyrics and a combination of both. Unfortunately, due to the scarcity of digitalized resources, Indian music fares poorly in music mood retrieval research. In this paper, we identified the mood taxonomy...

We report a statistical analysis of more than eight thousand songs. Specifically, we investigated the probability distribution of the normalized sound amplitudes. Our findings suggest a universal form of distribution that agrees well with a one-parameter stretched Gaussian. We also argue that this parameter can give information on music complexity, and consequently it helps classify songs as we...

Users leave digital footprints when interacting with various music streaming services. Music play sequence, which contains rich information about personal music preference and song similarity, has been largely ignored in previous music recommender systems. In this paper, we explore the effects of music play sequence on developing effective personalized music recommender systems. Towards the goa...