LOOK THROUGH YOUR MUSIC: FAST FOURIER TRANSFORM METHOD, MUST FOR A MUSIC STUDENT

For more music students to be research minded more scientific look through music is necessary during the bachelor studies itself. Music is one of those branches of studies which are looked at not very scientific. However, music contains plenty of Physics concepts and further technological ideas applied in music study would enhance students understanding of sound scientifically.
A sound created by any musical instrument is obviously first and foremost visualized as a waveform running forward with time. If ever they were shown this waveform on an oscilloscope the same note played on various instruments would look different in shape. The reason for this difference needs to be known by a musician to be able to have a fuller understanding of sound they produce. No doubt music in aural from is important, however this acoustic knowledge of the sound would help one analyze the sound generated, and thus could explore ones instrument further in a scientific and focused way. The paper presented here brings out this analysis by use of very easy to use software called sigview. This software creates affordable and flexible signal analysis solution based on Fast Fourier Transfroms (FFT). The user does not need to know in-depth information about FFT at all, but just enjoy the analyzed output with a very friendly to use software buttons. It can take in a variety of file formats including .WAV and MP3. Once the input file is fed to the programme, a spectrogram is available. This spectrogram is amplitude versus frequency plot of the piece of music fed in. The principle of FFT is used here: a time domain graph can be expressed as a sum of harmonic sinusoids. There lies some complex mathematics under this process of transformation from time domain to frequency domain. This concept is one of the rather difficult one to grasp as mentioned time and again by scientists and engineers since years together [1], however becomes much easier when available visually in this form.
The paper further gives example of a few spectrograms for a variety of instruments for comparison. A number of ways available in the software also are used for comparison and demonstration. A few samples of sound which have overtones are analyzed to give an idea of the feel of overtones in music. This knowledge is important to have as overtones create a different feel of the sound as well as they are important in music therapy [2].
1. An introduction to signal processing and Fast Fourier Transfrom (FFT) by Kevin J. McGee, 2009
2. Overtone spectra of gongs used I music therapy, by Eliezer Rapoport, Smadar Shatz, and Noa Blass, Journal of new music research, 2008