Bae, Byung Chull

Cheong, Yun-Gyung

Nelson, Mark

Scirea, Marco

This paper presents an empirical study that investigated if procedurally generated music based on a set of musical features can elicit a target mood in the music listener. Drawn from the two-dimensional affect model proposed by Russell, the musical features that we have chosen to express moods are intensity, timbre, rhythm, and dissonances. The eight types of mood investigated in this study are being bored, content, happy, miserable, tired, fearful, peaceful, and alarmed. We created 8 short music clips using PD (Pure Data) programming language, each of them represents a particular mood. We carried out a pilot study and present a preliminary result

Mood Expression in Real-Time Computer Generated Music using Pure Data

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