The purpose of this study was to investigate the content analysis of recent Persian songs (2013-2014) according to emotions of anxiety, depression, anger, fear and happiness. The research method was content analysis type. The sample consisted of 50 Persian songs from 2013 to 2014 which they were selected by simple sampling. To analysis of data, massages were categorized in emotions of anxiety, ...

In the music world, a mashup is a fusion of two or more pre-recorded songs. The songs are beat-matched, then selectively combined with audio filters and signal addition. Often, the vocals of one song are mixed over the beats, bass, and melody of another. Project Mashbot represents an attempt to automate this process while maintaining the aesthetic appeal found in mash-ups created by skilled hum...

Since numerous songs have recently been released increasingly, the genre of the song clustering is reasonably more important in terms of the audience’s choice. Also arguments for plagiarism are continuously being raised. For this reason, similarity measurement between two songs is important. In previous works, although similarity measurement has been actively researched in the field of query by...

In this paper, we introduce a novel parallel corpus of music and lyrics, annotated with emotions at line level. We first describe the corpus, consisting of 100 popular songs, each of them including a music component, provided in the MIDI format, as well as a lyrics component, made available as raw text. We then describe our work on enhancing this corpus with emotion annotations using crowdsourc...

Large music collections require new ways to let users interact with their music. The concept of finding ‘similar’ songs, albums, or artists provides handles to users for easy navigation and instant retrieval. This paper presents the realization and user evaluation of a music retrieval music that sorts songs on the basis of similarity to a given seed song. Similarity is based on a userweighted c...

Although personal tastes may change over time, overall people still enjoy music they have not listen to for some time or not very often. However, most solutions for browsing music collections do not focus on showing or suggesting these songs to create serendipitous rediscoveries. Instead they promote most recently played songs as an entry point for browsing and playing music. This way, users ar...

This paper builds an understanding how music is currently listened to by small (fewer than 10 individuals) to medium-sized (10 to 40 individuals) gatherings of people—how songs are chosen for playing, how the music fits in with other activities of group members, who supplies the music, the hardware/software that supports song selection and presentation. This fine-grained context emerges from a ...

As a result of the growth of online music streaming services, a large number of playlists have been created by users and service providers. The title of each playlist provides useful information, such as the theme and listening context, of the songs in the playlist. In this paper, we investigate how to exploit the words extracted from playlist titles for text-based music retrieval. The main ide...

Music recommendation services collectively spin billions of songs for millions of listeners on a daily basis. Users can typically listen to a variety of songs tailored to their personal tastes and preferences. Music is not the only type of content encountered in these services, however. Advertisements are generally interspersed throughout the music stream to generate revenue for the business. A...

This album combines garage punk with synth and electronic sounds. Most of the songs have an upbeat yet slightly off tune that is pleasant to listen to but is slightly unsettling as it is not the type of beat and notes that you typically hear in most music on the radio. The faster songs are definitely the best songs, as the fast beat tends to air best with garage and electronic sounds. The songs...