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Despite recent advances in audio content-based music emotion recognition, aquestion that remains to be explored is whether an algorithm can reliablydiscern emotional or expressive qualities between different performances of thesame piece. In the present work, we analyze several sets of features on theireffectiveness in predicting arousal and valence of six different performances(by six famous pianists) of Bach's Well-Tempered Clavier Book 1. These featuresinclude low-level acoustic features, score-based features, features extractedusing a pre-trained emotion model, and Mid-level perceptual features. Wecompare their predictive power by evaluating them on several experimentsdesigned to test performance-wise or piece-wise variations of emotion. We findthat Mid-level features show significant contribution in performance-wisevariation of both arousal and valence -- even better than the pre-trainedemotion model. Our findings add to the evidence of Mid-level perceptualfeatures being an important representation of musical attributes for severaltasks -- specifically, in this case, for capturing the expressive aspects ofmusic that manifest as perceived emotion of a musical performance.

On Perceived Emotion in Expressive Piano Performance: Further Experimental Evidence for the Relevance of Mid-level Perceptual Features