**5. Discussion**

In experiment 1, the color identification rate of Group A with six-color wheel codes used was 100%. Additionally, for Group B with eight-color wheel codes used, the color identification rate was 86.67%. In experiment 2, the color identification and the lightness rate of Group A and Group B was 100%. Additionally, in experiment 3, the color, lightness, and depth identification of participants were 95.56%, 99.26%, 95.93%. The overall recognition rate was very high and still performed well with multiple sound variables. However, because the number of colors in the eight-color wheel was more than that of the six-color wheel, the recognition rate was 13.33% lower than that of the six-color wheel. If the distinction between confused colors is strengthened, the recognition rate will be better.

In the workload assessment test, the six-color wheel codes scored 43.75 points, and the eight-color wheel codes scored 48.75 points; the total score was 46.25 points. The lower the rating, the less the load on the user. With a full score of 100, the overall score tended to be in the middle, i.e., the user load was medium. In the user experience test, the six-color wheel codes scored 72.32 points and the eight-color wheel codes scored 71.43 points. The higher the score, the better the user's sense of use. With a score of 100 out of 100, the overall score was good. As described in the Results section, the experiment may feel relatively loaded and difficult to use due to insufficient learning and familiarity with the design. Additionally, due to the excessive number of variables used in the experiment, there may be a degree of fatigue for the participants. Therefore, a better HRTF matching seems necessary, which will make the effect more visible, and the participants could more clearly distinguish the colors. Additionally, audio optimization to make the audio more accurate and friendly is also a method, while simplifying the design will also optimize the user's perception. Table 13 shows conflicting user feedback and future work to resolve the conflict.



This study has several advantages over other ones:


Through quiz tests and user evaluations, the sound code in future work could be improved in the following ways:

