Musical Influence Recognition
Throughout history, musicians have been heavily influenced by previous generations of artists. Frequently during inter- views, musicians mention older artists as the inspiration for a particular song or album. The Beatles, Jimi Hendrix, and James Brown have all had a far reaching impact on the current musical landscape. When asked, younger artists frequently cite the works of these and other older musicians as influential, for instance; Chris Brown has mentioned that one of his most important musical influences is Michael Jackson. One can go even further and trace Jackson’s influences to artists such as James Brown and Jackie Wilson. As another example of the importance of influence, entire genres of music have been formed from combining previous works from other genres. Some early rock musicians described the music they played as sped up blues. Early hip-hop artists would extend beat breaks of disco records and talk over them in the style of Jamaican toasting, which is the act of talking or chanting over a rhythm. By learning from and modifying previous musicians’ work, artists have shaped the evolution of music. However, little is known about the relationship between acoustic properties and the level of influence an artist obtains, or why certain musical concepts and ideas are more impactful than others and this is something that could benefit from further study.
By following the progression of influence from one musician to another we are provided with an interesting look at how music has changed over the years. This mapping of influence could potentially be used to augment music recommendation systems and also offer some useful information to the field of musicology, where information on artistic influences and relationships are heavily sought after. Eventually, knowledge of influence can help us learn more about music genres and how they have been combined to form other newer genres. However, it is difficult to clearly define influence, making it a particularly abstract task in music information retrieval (Music-IR).
- B. G. Morton and Y. E. Kim, “Acoustic Features For Recognizing Musical Artist Influence,” in International Conference on Machine Learning and Applications (ICMLA 2015), 2015.