We all probably have heard songs that sometimes sound quite strange, yet beautifully. When I was a child it was a mystery for me what makes a song sound so strange. During years I found my way to analyze songs, figure out the strange parts and see common patterns that are used in many songs.
Warning: This series might demystify the songs in you ears forever!
Oystein Sevag and Lakki Patey: Cahuita - an example of an amazing, strange and difficult song.
Since I collected notes about a lot of songs, in this series I'd like to share the results with you - in a comprehensible visual form. The goal is to enable anyone to learn about music by exploring.
One of the guiding principles is to have a problem before fiding solution. First learning a theory and then trying to apply to to analyze music is first having a solution ... (for WTF?) ... and then the problem. On the other hand by first exploring a song and then connecting it to the theory, the theory is immediately useful.
There's a whole range of songs of various difficulty. I believe in taking small steps. Trying to understand a complex concept from scratch is hard, learning it as a small step from a little less complex one is easy. By repeating we can make a path backwards to the easiest concepts.
The truth is that songs are quite similar and share rather a small number of patterns that appear thoughout the songs. The theory is just a way to describing those patterns so that we can identify them in new songs.
To make things simple in this series we'll mostly explore music from the point of view of harmony, ie. chords and their relationships. This is one of the main areas that contribute to the feeling that a particular place in song sounds mysteriously. A whole different view might be on rhythm, melody, form, style, timbre, lyrics and other aspects. In future we might explore those as well.
The Beatles: Penny Lane - an interactive visualization.
In this series we will try to cover a wide range of songs. However, there's a notable group of songs - by The Beatles - that will get a lot of attention. The reasons are two: (1) their songs are very beautiful and rich in the patterns to explore and (2) there's an awesome dataset that can be used to make great visualizations without much effort.
I'd be glad if this series helps you to better understand what's going on in the music and appreciate its beauty. Also please feel free to comment and send you own wishes for songs to be analyzed.
So what do you think? Did I miss something? Is any part unclear? Leave your comments below.