Design of Sporty SQI using Semantic Differential and Verification of its Effectiveness

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1 Design of Sporty SQI using Semantic Differential and Verification of its Effectiveness Gahee KWON 1 ; Jae Hyuk PARK 1 ; Han Sol PARK 1 ; Sang Il LEE 2 ; Yeon Soo KIM 3 ; Yeon June Kang 1 1 Seoul National University, Republic of Korea 2 Hyundai Motor Company, Republic of Korea 3 Daedong Movel System Company, Republic of Korea ABSTRACT The Sporty Sound Quality Index(SSQI), which evaluates how sporty an automotive engine sound, can be expressed in psychoacoustic metrics such as loudness and sharpness through jury evaluation and measurement of the psychoacoustic metrics of sound sources. During jury evaluation, however, juries have difficulty rating their feelings because the meaning of the word, Sporty, is complicated and can be interpreted in various ways. In this study, the Semantic Differential(SD), which can disassemble complex adjectives into simpler words, is used to address this problem. As a result of a jury evaluation using SD, loudness and sharpness were selected to represent the SSQI, while the jury evaluation without SD chose loudness only. To verify the effectiveness of the two types of SSQI, an additional jury evaluation with new engine sound samples was conducted. The high correlation between sporty scores estimated using the SSQI developed with SD and the results of the additional jury evaluation shows that SD is meaningful for designing SSQI. Keywords: Sound Quality Index, Jury Evaluation, Semantic Differential I-INCE Classification of Subjects Number(s): INTRODUCTION As inside-vehicle noise control technology has been improved, undesired vibration and noise in the vehicle has been extremely reduced. Nevertheless, the importance of noise and vibration problems has increased. It is impossible to totally eliminate the noise and vibration in a vehicle, so inside-vehicle noise always exists even after noise control. In this context, focusing on the enhancement of the inside-vehicle sound quality, rather than noise reduction, has been suggested recently to increase user satisfaction. Furthermore, research on the enhancement of sound quality can be applied to designing inside-vehicle sound to target image or user satisfaction. To develop a Sporty car, for example, the developer can concentrate on the improvement of the sound quality in addition to the exterior design or engine performance. Although sound quality is an exceedingly subjective concept, people tend to trust the results of an objective test, such as the measurements of sound pressure levels, rather than results of subjective evaluations of sound quality, e.g., a jury evaluation. In other words, it is difficult for research on sound quality to be considered reliable without the analysis of objective data, such as experimental values. Hence, the results of a subjective evaluation of sound quality need to be connected to objective data to ensure its reliability. To be specific, a subjective evaluation such as a jury evaluation should be connected to measurement values such as psychoacoustic metrics. In this context, the Sound Quality Index(SQI) is the connection of subjective data such as evaluation scores and objective data such as psychoacoustic metrics. SQI is usually specified by regression analysis. In other words, the evaluation scores of each sound sample can be connected to its psychoacoustic metrics using regression analysis. 1 hellokh333@snu.ac.kr 2 silee72@hyundai.com 3 yskim@ddmvs.co.kr 6722

2 During a jury evaluation, however, many juries have difficulty assessing the Sporty qualities of a sound because they are confused about the meaning of Sporty and about what they are supposed to evaluate. Meanwhile, because of the lack of a clear criteria for the structure of a SQI jury evaluation, the design of experiments and evaluation items are difficult to determine for some researchers. The Semantic Differential(SD), which disassembles complex words into simpler words, is known as one solution to address the ambiguousness of evaluation items. However, the effectiveness of SD when designing a sporty SQI (SSQI) has not yet been completely proven. Therefore, this paper focuses on the development of SSQI and its methodology, especially on the role of the SD in order to clarify the necessity and effectiveness of SD for designing SSQI. 2. DEVELOPMENT OF SSQI 2.1 Sound Samples for Jury Evaluation Figure 1 Recording the engine sound of a running car Table 1 Psychoacoustic metrics of samples Sample no. Loudness Roughness Sharpness Tonality For the jury evaluation, the engine sounds of four cars were recorded. To reflect the characteristic of the human hearing system, a dummy head inside the vehicle recorded the engine sounds. Next, four samples were modified using several filters that modified the signal in various ways, such as 6723

3 increasing the sound pressure over the whole frequency band, generating 10 more samples. Therefore, 14 samples were used for jury evaluation, and the psychoacoustic metrics of each sample were measured. Because loudness, sharpness, roughness, and tonality seemed to be related to engine sound, these metrics of each sample were calculated as shown in Table SD SD separates complex and ambiguous words into simple and easy words to help understanding. A complex word is separated into pairs of adjectives that have the opposite meaning to each other, for example, Big-Small and Sharp-Smooth. Pairs of adjectives consist of words that are closely related to the complex word. In according to Osgood, who devised the SD, a pair of adjectives can be made up of adjectives that are connotatively and common-sensically related to the object of SD, the complex word. Using SD, researchers can separate their complicated evaluation item into easy words, then they can help juries to score each criterion, which is a much easier process to understand than before. It is easier to evaluate how Sharp a sound is than how Sporty a sound is, and thus, juries can establish a better understanding of the evaluation standard. To apply the SD to the process of jury evaluation for designing a SSQI, Sporty needs to be separated into simpler words that are connotatively related to Sporty. Considering the purpose of this experiment and with engineering sense, Sporty was disassembled into Strong, Sharp, Dynamic, Overwhelming, Three-dimensional, Thick, and Clear. 2.3 Jury Evaluation To verify whether the SD causes differences or not, a jury evaluation was carried out for two days. On the first day, juries evaluated engine sound samples with an assessment scale that used Sporty only. The next day, they evaluated the same samples with the assessment scales as six pairs of adjectives. All of the tests were on a scale of 1 to 7, and the two types of evaluation form are shown in Figures 2 and 3. The sound samples were given to juries randomly and only the sample number was allowed to be disclosed. Twenty-three juries participated in this jury evaluation. Table 2 shows the result of jury evaluation without using the SD, and Table 3 shows the result of jury evaluation using the SD. Table 2 Result of Jury Evaluation Sample no. Sporty score

4 Figure 2 Evaluation Form for the Sporty Score Figure 3 Evaluation Form for the Sharp-Smooth Score Table 3 Results of Jury Evaluation Adjectives Scores Sample Strong Sharp Dynamic Over-whel 3-Dimen-si Thick Clear no. ming onal Development of SSQI Using Regression Analysis Two types of SSQI were developed using regression analysis, one using the SD and one without. Table 4 presents the results of regression analysis between the Sporty scores and psychoacoustic metrics of each sample. Equation (1) is the SSQI without the SD, which is referred to as the direct SSQI. It shows that Loudness is the most dominant and only factor of SSQI. In contrast, Table 5 shows the relations between the Sporty scores and scores of the adjective pair scales that were used for jury evaluation using the SD. Tables 6, 7, and 8 show the relations between each adjective and the psychoacoustic metrics. Model 3 in Table 5 indicates the final model of regression analysis by repeated variable selection and removal. At a level of 5%, the significance of Constant in Model 3 could be problem. However, we decided to admit a level of 5.2%, which is slightly beyond the criterion of 5%, to take into account as many adjectives as possible. Hence, regression Model 3 was chosen to develop the SSQI, and Equation (2) is the SSQI using the SD. It shows that not only Loudness has an effect on how Sporty the sound of a vehicle is, but Sharpness is also a critical factor. 6725

5 (1) (2) Table 4 Regression analysis for the Sporty-Psychoacoustic metrics Coefficient Standard error Significance probability Constant Loudness Table 5 Regression analysis for Sporty - Adjective pairs Model Coefficient Standard error Significance probability 1 Constant Dynamic Constant Dynamic Sharp Constant Dynamic Sharp clear Table 6 Regression analysis for Dynamic-Psychoacoustic metrics Coefficient Standard error Significance probability Constant Loudness Table 7 Regression analysis for Sharp-Psychoacoustic metrics Coefficient Standard error Significance probability Constant Sharpness

6 Table 8 Regression analysis for Clear-Psychoacoustic metrics Coefficient Standard error Significance probability Constant Sharpness Loudness Effectiveness Verification 3.1 Necessity of an Effectiveness Verification Because each type of SSQI selected different variables and coefficients, we need to verify which one is better to estimate the Sporty scores of vehicle sounds. To compare the two types of SSQI, an additional jury evaluation with new samples was carried out. 3.2 New samples For the additional jury evaluation, new sound samples were recorded. As shown in Figure 1, a dummy head inside the vehicle was used for recording. Different engine sounds for the vehicle were recorded by changing its muffler. Four types of mufflers were used to make four samples. Each sample was modified using five filters, e.g., low pass filter. Similar samples that were difficult to distinguish were deleted, and thus 12 distinguishable samples were made. Next, the loudness, roughness, sharpness and tonality of the new samples were measured. Table 9 shows the psychoacoustic metrics of the new samples. Table 9 Psychoacoustic metrics of the new samples Sample no. Loudness Roughness Sharpness Tonality

7 3.3 Additional Jury Evaluation For the additional jury evaluation, we organized a new evaluation group. The new juries consisted of 11 students majoring in acoustics and mechanical vibrations. They evaluated new 12 samples, using the seven-point scale. In this section, the SD was not applied, so they considered only whether the sound sample was Sporty or not. At the same time, the Sporty scores of each sample were estimated by two types of SSQI, using the psychoacoustic metrics of each sample. For example, because the loudness of sample 1 is 17.3, its Sporty score can be estimated at using. Table 10 shows the estimated Sporty scores using both types of SSQI and the real Sporty scores of the additional jury evaluation. In Table 10, refers to the scores estimated by Equation (1), and denotes the scores estimated by Equation (2). The real scores are the Sporty scores obtained by the additional jury evaluation. Table 10 Estimated and real scores Sample no. Real Scores Correlation Analysis Result A correlation analysis was performed on the estimated scores and real scores, and the correlation coefficients of both SSQI types are compared in Table 11. A high correlation coefficient implies that the estimated values are well matched with the real values. As shown in Table 11, the correlation coefficient between the scores estimated by and the real scores is higher than that of ; hence, we conclude that SSQI with SD is more accurate than direct SSQI. Table 11 Result of the Correlation Analysis Correlation coefficient CONCLUSIONS In the first jury evaluation, we developed two types of SSQI using 14 sound samples. SSQI using the SD selected Loudness and Sharpness as its factors. However, direct SSQI selected Loudness only. To verify the effectiveness and necessity of the SD, an additional jury evaluation with new samples 6728

8 was carried out. Correlation analysis was used to compare the accuracy of each type of SSQI; the correlation coefficients between the Sporty scores estimated by each SSQI and the real Sporty scores were calculated. As a result, the correlation coefficient between scores estimated by and the real scores was higher than that of. This implies that is better and more accurate representation of the Sporty sound quality. Ultimately, we conclude that using SD during jury evaluation is effective and necessary in order to more specifically determine how people judge their feelings about the sporty qualities of a vehicle sound. ACKNOWLEDGEMENTS This research was supported by Hyundai Motor Company, Daedong Movel System Company and Ministry of Trade, Industry and Energy. We would like to thank all of the participating researchers for their invaluable effort and helpful suggestions on this project. REFERENCES 1. Osgood Charles E. The Nature and Measurement of Meaning. Psychological Bulletin. 1952; 49(3): Fastl Hugo. Communication Acoustics, Germany: Springer Berlin Heideberg; p Bodden Markus. Instrumentation of Sound Quality Evaluation, Acta Acustica united with Acustica. 1997; 83(5): Kang J., Zhang M. Semantic differential analysis of the soundscape in urban open public spaces. Building and Environment. 2010;45(1):