Neural-Network-Based Account of Affective Phenomenon Caused by Odd Number of Acoustic Beats

Abstract

Three-beat sounds are widely used in cheering. Five- or seven-syllable phrases are used in traditional Japanese and Chinese poems. Odd numbers of short sounds seem to relate to an interesting affective phenomenon. Our psychological experiment conducted with various numbers of beats shows that a three-beat sound is the most exciting sound for people. We propose a neural-network model that relates to such a phenomenon. It is realized by the combination of neural networks with reciprocal-inhibition and cascade structures. We additionally take into account the effect of attention fluctuation. We simulate the neural-network operation, indicating that degree of excitement of the model takes the highest level for three beats. This result is confirmed to be consistent with our experimental result. Under the condition that the attention fluctuation is suppressed, the degree of excitement in the simulation takes higher levels for odd numbers of beats than even numbers of beats. This seems to relate to the ground of five- or seven-syllable phrases used in traditional Japanese and Chinese poems.