Sample Qin #3 – Suxin Silk Strings 5, 6, and 7 Comparison Data


Here you will find an additional datasets for Sample Qin #3 using Suxin silk strings 5, 6, and 7 as a reference for other comparisons. If you are not familiar with this particular qin on this site, you can find additional information, as well as a complete string set dataset, by clicking the link to the Sample Qin #3 page main page. The recordings for this set of data was generously taken by it’s owner and sent to me for analysis. Strings 5, 6, and 7 were recorded for a comparative analysis between the response of Suxin silk strings on this qin and Sample Qin #4, as well as a reference for other comparisons between these qin and string combinations and other strings, such as Longren Binxian strings, and primarily, my current best set of experimental twisted nylon “Fire Strings”, which I have only made for strings 5, 6, and 7. The tuning chosen for this dataset is the standard modern tuning of C. If you would like to see the data for for the same Suxin silk strings on a different qin, click on the link to the Sample Qin #4 – Suxin Silk Strings 5, 6, and 7 Comparison Data page.

The graphs below are the harmonic content data, spectrograms, and autocorrelation graphs for the tested Sample Qin #3 strung with Suxin silk, for strings 5, 6, and 7, externally recorded, with the specified tuning and technique 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.