## 7 Conclusions, Limitations, and Future Works
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Arousal**} & \multicolumn{3}{c}{**Valence**} \\ \cline{2-7}
**Personality** & **Aud. vs.** & **Aud. vs.** & **Phy. vs.** & **Aud. vs.** & **Aud. vs.** & **Phy. vs.** \\  & **Phy.** & **Comb.** & **Comb.** & **Phy.** & **Comb.** & **Comb.** \\ \hline Openness (L) & – *** & + & + *** & – *** & – *** & + *** \\ Openness (H) & – *** & – * & + *** & + & + *** & + *** \\ Conscientiousness (L) & – *** & – & + *** & – & + & + *** \\ Conscientiousness (H) & – *** & + *** & + & + *** & + *** & + *** \\ Extraversion (L) & – *** & – *** & + *** & – & – & + ** \\ Extraversion (H) & – *** & + & + *** & + & + *** & + *** \\ Agreeableness (L) & – *** & – & + *** & – & + *** & + *** \\ Agreeableness (H) & – *** & + & + *** & + *** & + *** & -* \\ Emotional stability (L) & – *** & + & + *** & – & + *** & + *** \\ Emotional stability (H) & – *** & – & + *** & + & + *** & + \\ \hline \hline \end{tabular} Notes: The Benjamini–Hochberg procedure was applied to control Type I error when comparing classification performance (* \(p<0.05\), *** \(p<0.01\), *** \(p<0.001\)). The “+/”/—” signs indicate the latter feature set performed better/worse than the former one. Aud. = Audio-only, Phy. = Physiology-only, Comb. = Combined.  
\end{table} 
Table 8: Comparison of classification performances on different modalities in group-wise modeling. being dominated by the positive class, especially for the valence dimension. This data unbalance toward positive valence might be attributable to the experiment design where participants searched and selected music to listen to rather than listening to preselected music. While this experiment design addresses the MIR contexts, it would result in more music favorable to the listeners being included in the dataset. Future work could explore personalized models if larger datasets could be constructed with more listening history and corresponding physiological signals from each user. In the experiment setup, album covers and song metadata were displayed on screen, albeit in small sizes, when music was played. This setup conforms to the norm of online music services but does introduce potential influence from visual information on listeners' perception of the song. Future studies may avoid this by displaying a blank screen when music is played, trading off the ecological authenticity of the user interface. Given that different physiological signals may reinforce each other, future research is much needed to investigate the contribution each physiological signal makes to the outcome. More work is also suggested to exploit other personal and situational factors beyond personality that may play a role in ones' affective perception of music, such as music training background and/or tasks at hand. Last but not least, it is noteworthy that, as physiological signals and audio signals are both time series data, a multimodal time series approach could thus be exploited for many interesting research topics, such as detecting variation of music-induced emotion within the course of a music piece. Conceptualization, X.H. ; Data curation, X.H. and R.L. ; Formal analysis, F.L. ; Funding acquisition, X.H. ; Investigation, X.H. and R.L. ; Methodology, X.H. ; Project administration, X.H. ; Software, X.H. and R.L. ; Supervision, X.H. ; Validation, X.H. and F.L. ; Writing--original draft, X.H. and F.L. ; Writing--review and editing, X.H., F.L. and R.L. All authors have read and agreed to the published version of the manuscript. This study is supported by National Natural Science Foundation of China (No. 61703357) and the Research Grants Council of the Hong Kong S.A.R., China (No. HKU 17607018). The study was conducted in accordance with the Declaration of Helsinki and approved by the Human Research Ethics Committee (HREC) of The University of Hong Kong (protocol code EA1802092, approved on 29 March 2018). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.