## 1 Introduction
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Author** & **Year** & **Objects of Evaluation** & **Evaluation Terms** \\ \hline [PERSON] [12] & 1958 & 20 different passive sonar sound & 50 pairs \\ \hline [PERSON] [13] & 1974 & 35 voiced and unvoiced speech sounds, musical sounds & 30 pairs \\ \hline [PERSON] and [PERSON] [14] & 1976 & \begin{tabular}{c} Orchestral instrument (including string, \\ woodwind, and brass) \\ \end{tabular} & 19 \\ \hline [PERSON] et al. [15] & 1991 & \begin{tabular}{c} 4 performances of the Promenades in \\ “Pictures at an Exhibition” \\ \end{tabular} & 60 \\ \hline [PERSON] and [PERSON] [16] & 1994 & \begin{tabular}{c} Sound generated by an \\ electronic synthesizer \\ \end{tabular} & 124 \\ \hline [PERSON] et al. [17] & 1996 & \begin{tabular}{c} 12 synthetic Western traditional \\ instrument sounds \\ \end{tabular} & 23 \\ \hline [PERSON] and [PERSON] [9] & 1997 & 24 music excerpts from CDs on the market & 18 pairs \\ \hline [PERSON] and [PERSON] [18] & 1997 & \begin{tabular}{c} Western orchestral instruments, tuning fork, \\ organ, and softly sung sounds. \\ \end{tabular} & 21 \\ \hline [PERSON] et al. [19] & 1999 & \begin{tabular}{c} “A” major scale playing on the violin \\ (including 3 bow force, 3 bow speed, and 3 \\ sounding point) \\ \end{tabular} & 20 \\ \hline [PERSON] et al. [20] & 2000 & \begin{tabular}{c} 48 systematically controlled synthetic \\ auditory warning sounds \\ \end{tabular} & 16 pairs \\ \hline [PERSON] and [PERSON] [21] & 2003 & \begin{tabular}{c} 4 recordings of different organs \\ \end{tabular} & 7 \\ \hline [PERSON] and [PERSON] [22] & 2003 & \begin{tabular}{c} Orchestra instrument (including bow, wind, \\ and keyboard) \\ \end{tabular} & 30 \\ \hline [PERSON] [23] & 2004 & \begin{tabular}{c} 170 sonar sounds (including 23 different \\ generating source types, 9 man-made, and \\ 14 biological) \\ \end{tabular} & 148 \\ \hline [PERSON] and [PERSON] [24] & 2005 & \begin{tabular}{c} 9 distorted guitar sound (including three \\ nominal distortion types) \\ \end{tabular} & 11 pairs \\ \hline [PERSON] et al. [25] & 2006 & \
\begin{tabular}{c} 12 instrument samples from the McGill \\ university master samples (MUMS) library \\ (including woodwind, brass, string, \\ and percussion) \\ \end{tabular} & 15 \\ \hline [PERSON] [26] & 2006 &
\begin{tabular}{c} Violin sounds of tones B3, \#F4, C5, G5, and \\ D6 played using the same technique \\ \end{tabular} & 25 \\ \hline [PERSON] and [PERSON] [27] & 2007 & Music recording work & 27 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Previous studies on timbre evaluation terms. Timbre contains complex information concerning the source of a sound. Humans can perform a series of tasks to recognize objects by listening to these sounds [38]. As such, the quantitative analysis and description of timbre perception characteristics has broad implications in military and civil fields, such as instrument recognition [39], music emotion recognition [40], singing quality evaluation [41], active sonar echo detection [42], and underwater target recognition [43]. Developing a mathematical model of timbre perception features is vital to achieving a quantitative description of timbre. Two primary methods have conventionally been used to quantify timbre perception features. The first is the concept of psychoacoustic parameters [6]. That is, by analyzing the auditory characteristics of the human ear, a mathematical model can be established to represent subjective feelings, such as sharpness, roughness, and fluctuation strength [44]. Since most of the experimental stimulus signals in these experiments were noise, the calculated value for the musical signal differed from the subjective feeling, which is both limited and one-sided. Another technique combines subjective evaluation experiments with statistical analysis. In other words, the experiment is designed according to differences in perceived features from sound signals, from which objective parameters can be extracted.