6.5 Results

Table 6.2: Legend of the factors included in the analyses presented in Section 6.5, particularly in Tables 6.3-6.6.

6.5 Results

Here I will discusses the results obtained in this study. First, the considerations taken in the analysis will be presented. Next, in line with the main aims of this study, we will analyze the combined discriminative power of both the combination of features (i.e., repeated measures MANOVA (Wilks’ lambda)) and the features separately (i.e., (univariate) repeated measures ANOVA (Huynh-Feldt)). This will be done for two series of analysis, one to assess the dimensional VA model and one to assess six discrete basic emotions. The factors included in the analyses are: environment, the personality traits neuroticism and extroversion, and gender; see also Table 6.2.

6.5.1 Considerations with the analysis

The preliminary analysis of the ECG signal showed that the SD, the variance, and MAD of the heart rate (see Eqs. 5.5 and 5.6) provided similar results. This is in line with both the study presented in Chapter 5 and what is reported in the literature [349, 435]. Also with the current study, we have taken the SD of the R-R intervals as measure for HRV; see also Figure 5.2. Consequently, from this point on, the SD of the R-R intervals will simply be denoted as HRV.

The following factors were also included in the analysis: the environment (i.e., office versus living room), gender, and the two personality traits extroversion and neuroticism. Preliminary analysis showed that the other recorded demographical information (e.g., age; see Section 5.4 of Chapter 5) did not influence the emotional responses of the participants. Hence, this information was excluded from further analyses (cf. Figure 5.2).

As measure of effect size partial eta squared (η2) will be reported to indicate the proportion of variance accounted for (i.e., a generalization of r/r2 and R/R2 in correlation/regression analysis) [737]. The threshold for reporting results is the same as for the study reported in Chapter 5: p ≤ .010 and, hence, ensures reliable results.

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Table 6.3: Results of the repeated measures MANOVA on the valence-arousal (VA) model and its distinct dimensions. The threshold for significance was set to p ≤ .010.

6.5.2 The (dimensional) valence-arousal (VA) model

In Table 6.3 the results of a repeated measures MANOVA are presented that mapped the four features derived from the speech and ECG model onto the dimensional VA model. Results of both the integral VA model and its two dimensions are presented. Table 6.3 denotes that 43% of the variance of the VA model can be explained with the MANOVA. The results on the distinct dimensions confirm this result with respectively 38% and 57% (when including gender) explained variance for the valence and arousal dimensions.

When the factor gender was included in the analysis, good results were obtained as well. However, including the factors environment and the personality traits neuroticism and extroversion only seemed to add noise to the MANOVA model. The power of the MANOVAs and the explained variance were much lower than when these factors were included. All in all, the assessment of emotions based on the VA model using the four features selected seemed to be robust with respect to influences of environment (or context) and personality traits.

To unravel the influence of each of the four features, a repeated measures ANOVA was executed for each of them. The results of these analyses are presented in Table 6.4. These analyses provide a much more subtle image of the features included in the MANOVA. We will now first discuss the results on the three speech features (i.e., SD F0, intensity I, and energy E) and, subsequently, the ECG feature HRV.

SD F0 was shown to have a good predictive power and was able to explain almost respectively 31% and 42% of all variance for the valence and arousal dimensions of the VA model (when combined with gender information); see Table 6.4. In contrast, for the complete VA model SD F0 had little predictive power. Additional information reduced the power of the model instead of improving it. Effects that exceeded the threshold were not found in any of the analyses for either arousal or valence on the I or the E.

In the perspective of the VA model, HRV has been reported to indicate both the experienced valence and the experienced arousal. These results were firmly confirmed by the current study; see Table 6.4. Sixty-two percent of all variance in the VA model was explained by solely the HRV of the participants. With 58% explained variance for the valence dimen-

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Table 6.4: Results of the repeated measures ANOVAs on the valence-arousal (VA) model and its distinct dimensions. The threshold for significance was set to p ≤ .010. For the Intensity (I) and Energy (E) of speech no results are reported as none of them exceeded the threshold.

sion, this dimension seems to have contributed most to this result. For the arousal dimension effects were only found in interaction with gender and either environment or the personality trait extroversion; see Table 6.4. The explained variance of both the VA model and its dimension valence decreased when additional factors were taken into account. Hence, the complete model as well as one of its dimensions was not sensitive to various interpersonal factors, which is very convenient for many applications.

6.5.3 The six basic emotions

Table 6.5 presents the results of a repeated measures MANOVA that mapped the four features derived from the speech and ECG model onto the six basic emotions. The MANOVA showed an effect of the four features on the six basic emotions, with and without other factors included. Table 6.5 denotes that with the MANOVA 21% of the variance of the six emotions can be explained, which is not much. When other factors are included in the analysis, the power of the analysis declines significantly. Effects of the personality traits neuroticism and extroversion were not found at all. So, the combination of the four features explains

Table 6.5: Results of the repeated measures MANOVA on the six basic emotions. The threshold for significance was set to p ≤ .010.

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little of the variance between the six basic emotions. However, the model obtained is robust to the various factors included in this study and, hence, as such is robust.

To gain understanding of the influence of the four features, repeated measures ANOVAs were executed for each of them. The results of these analyses are presented in Table 6.6. First, we will discuss the results of the speech features SD F0. Second, the results of the ECG feature HRV will be discussed. In none of the analyses were the speech features intensity I and energy E or the personality traits neuroticism and extroversion shown to be of any influence; therefore, these features and factors will not be mentioned further on.

SD F0 by itself was shown to have insufficient power; see Table 6.6. Only when the factors gender with or without the personality trait extroversion were taken into account was an effect found. However, even then the explained variance was limited. The speech features intensity I and energy E were shown to have no predictive power at all, neither by themselves nor in combination with other factors; see Table 6.6.

As with the VA model, HRV was also shown to have a high predictive power for the six basic emotions: 57%. When the additional factors were included in the analysis, the explained variance dropped sharply. So, HRV was shown to be robust with respect to environment, personality traits, and gender.

6.5.4 The valence-arousal (VA) model versus basic emotions

When both emotion representations are compared, the following ten main conclusions can be drawn:

•Both emotion representations can handle the variation in participants, even without including additional information such as the environment, personality traits, and gender; see Tables 6.3- 6.6.

Table 6.6: Results of the repeated measures ANOVAs on the six basic emotions. The threshold for significance was set to p ≤ .010. For the Intensity (I) and Energy (E) of speech no results are reported as none of them exceeded the threshold.

E PN PE G Specification of effect SD F0

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•A high amount of variance can be explained using the VA model: 43%. This is much higher than with the basic emotions: 21% (cf. Tables 6.3 and 6.5).

•Many more effects were found with the VA model compared to the basic emotions as representation for emotions (cf. Tables 6.3 and 6.5 and Tables 6.4 and 6.6).

•The SD F0 was shown to have a good predictive power with both emotion representations; see Tables 6.4 and 6.6.

•The intensity (I) did not contribute to the predictive power of either of the two emotion representations; see Tables 6.4 and 6.6.

•The energy of speech (E) did not contribute to the predictive power of either of the two emotion representations; see Tables 6.4 and 6.6.

•The ECG feature HRV by itself was shown to be able to explain a high amount of variance for both the VA model (62%) and the six basic emotions (57%). For the VA model, this result can be mainly attributed to the valence dimension for which 58% of the variance was explained; see Tables 6.4 and 6.6.

•The personality traits neuroticism and extroversion had no significant influence on the participants’ experience of emotions; see Tables 6.3- 6.6.

•Gender was shown to interact with both models, often in combination with other factors. So, gender plays its role; however, what this is cannot be unveiled with the current data.

•Both the VA model and the basic emotions, as treated in this chapter, share many characteristics. This is mainly because a discrete representation of the VA model was used that can distinguish six compounds, similar to the six basic emotions.

This study replicated the study presented in Chapter 5 in its comparison of these two representations. The data of the current study confirmed the findings of the previous chapter that the VA model is most appropriate, as the explained variance is much higher than with the basic emotions: 43% versus 21%. The current results suggest that there is possibly no such thing as a basic emotion (cf. [202]). At best, as with the study in Chapter 5, the discrepancy in explained variance of the present analyses (cf. Tables 6.3-6.6) can be attributed to the variance of the stimuli within one category of one basic emotion. More than anything else this again illustrates the complexity of people and their emotional states. Moreover, this also explains the variation in results reported in the literature, in particular in research that goes from lab to life [674, 680].

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