Usage Classification of Onomatopoeia using Acoustic Features with Accent Position

Abstract

Onomatopoeias can sensitively and concisely express concepts that are difficult to verbalize sensitively and concisely. Interactive AI, such as smart speakers, are becoming increasingly important, but it is difficult for them to understand the subtleties of new onomatopoeias or onomatopoeias that are unique to a particular person. Our work attempted a more practical classification of onomatopoeic usage by focusing on the accent position in speech onomatopoeia, with reference to a previous work. As a result, our work can achieve higher classification accuracy than in a previous work.