Personal Qin w/ Tobaya Silk Strings


Below are the various datasets and graphs I have collected for an older set of Tobaya silk strings I have had the opportunity to borrow and test. Unfortunately the set was missing string #2, but it still provided me with very valuable data nonetheless. From what I was told, these Tobaya strings are the version of their silk strings prior to adding the external wrapping to them of later sets. So these strings, unlike most of the silk strings I have tested, have no outer wrapping on the thicker strings 1-4. That being said, testing them on my qin, I did not find this to be detrimental to the tone and playability of the strings – despite the common belief and practice that overwrapping is usually necessary on silk strings, these are an example of ones (in my own opinion) that work quite well as they are. They were also one of my more favorite sets to test. The strings were well played and worn in prior.

The graphs below are the harmonic content data, spectrograms, and autocorrelation graphs for the tested Tobaya silk strings, with the tuning and technique specified for each data set. You can enlarge the images by clicking on the thumbnails. At the bottom of the page is a brief description of each set of data.


DATA

1. Linear Spectrum Harmonic Content Graphs

 

2. Autocorrelation

 

3. Spectrograms (Window 4096)

 

4. Spectrograms (Window 2048)

 

5. Spectrograms (Window 512)


DATA DESCRIPTIONS

  1. Linear Spectrum Harmonic Content Graphs – Shows the harmonic content of each string, graphed along the linear spectrum in terms of frequency to intensity. A very accurate way to easily visualize the harmonics and overtones of each string.
  2. Autocorrelation – Shows the periodic nature or trends from a given set of data. Autocorrelation can provide a unique look at data, and can reveal repeating patterns from seemingly random datapoints. For this application, it is derived from the original signal and more clearly shows the decaying oscillatory nature of the plucked string.
  3. Spectrograms (Window 4096) – Shows the spectrogram of each string, with a window setting of 4096. This setting allows one to clearly view all of the harmonics by showing the frequency, intensity, and duration of each harmonic. This graph can be most easily cross-correlated to the linear spectrum harmonic content graphs to compare durations and intensities of harmonics in a string.
  4. Spectrograms (Window 2048) –  Shows the spectrogram of each string, with a window setting of 2048. For this application, I have found that this setting is ideal in viewing the oscillatory instabilities of the guqin string more clearly, which cannot be seen as well in higher window settings. These are seen as wavering lines, which are most noticeably present in the mid-upper harmonics.
  5. Spectrograms (Window 512) – Shows the spectrogram of each string, with a window setting of 512. For this application, I have found that this setting, while having the lowest frequency band resolution of the three settings, allows one to zoom out on the entirety of the harmonic spectrum, and see how the overall power level and intensity shifts from one string to another, and where the harmonic content is overall most present for a given string.