Searching for New Sound - Music Composition ideas

In the world of music analysis and signal processing, the Fourier transform is a powerful tool for understanding the frequency content of a sound. One of the key components of the Fourier transform is the window function, which controls how long the computer "looks" at the signal in order to determine the frequencies present. In a perfect world, a longer observation time would provide better accuracy in identifying the frequencies present in a sound. However, in the real world, musical notes from instruments are not infinitely long and their sustain is not always perfectly flat and clear. As a result, the pitch of a note can fluctuate, which can lead to a noisy spectrum when analyzing the sound. To address this problem, different window functions have been developed to control the observation time and minimize the impact of pitch fluctuations on the analysis. In music analysis, this principle can be applied to the frequency and time domain of a sound. A commonly used window f...

When the cluster is played in the low register, the harmonics of notes in the cluster interfere with each other. It creates a complex and muddy sound. The notes can be too close to each other and it can be hard to differentiate them, also the sound produced might be too dense and lack clarity. The low interval limits refer to the range of notes or pitches that are considered to be in the lower register of an instrument or voice. These limits are often established by composers and performers as a guide for creating and playing music in a specific range. For example, a composer may choose to avoid using certain intervals, such as a major third or minor second, below a certain pitch, D3 or E3 respectively, in order to produce a clear perception of an interval. The low interval limits are not hard rules, but more like guidelines, and can be broken depending on the creative intent. Some composers and performers may choose to use lower pitches and intervals in order to produce a specific...

 The combination tone effect is discussed in the previous article. In short, when two tones are played in the high range, our brain will make a low frequency as a fundamental frequency. I developed a program here on Github. Two playing frequencies are fa and fb. fb>fa The fundamental frequency is f1 . n is number of partials The fa and fb frequencies are considered two successive harmonics of fa = n*f1 and fb = (n+1)*f1.   For example, the main, 1000Hz and 800Hz are playing at the same time, in the previous article , the result is 200Hz, and the program returns a perfect fit message. If the pair with no harmonic relationship, the program tries all possible partials from 1 to 24, to find the closest result of the fundamental. The main v2 can work with complex harmonic partials and inharmonic partials, up the 4 partials, both found down in harmonic series patterns. All individual partials are treated as a pair of sine tones, performing the same process above and f...

In order to draw the dissonant curve of a spectrum, loudness is a considered factor in the equation. The measurement of loudness in the equation is in sone. This loudness scale is based on a large number of laboratory tests in which people were asked to adjust the intensity of one pure tone until they judged it to be 'half the loudness' of another tone of the same pitch and fixed intensity. This scale is subjective based. However, the human ears respond to loudness irregularly. We are tuned to listen to the vocal range and mid-high frequency. The equal-loudness contour displays the pattern of our hearing. With the same sound pressure level (SPL), with different frequencies, the loudness we perceive is different. On the other hand, we cannot distinguish the loudness difference in high volume (high SPL); but we can sense more loudness change in lower SPL. The measurement of SPL is in Pascal and is often presented in logarithmic scale (dB), while sone is a linear scale. Sethares ...