Academy & Industry Research Collaboration Center (AIRCC)

Volume 11, Number 23, December 2021

Extraction of Linguistic Speech Patterns of Japanese Fictional Characters using Subword Units


Mika Kishino1 and Kanako Komiya2, 1Ibaraki University, Japan, 2Tokyo University of Agriculture and Technology, Japan


This study extracted and analyzed the linguistic speech patterns that characterize Japanese anime or game characters. Conventional morphological analyzers, such as MeCab, segment words with high performance, but they are unable to segment broken expressions or utterance endings that are not listed in the dictionary, which often appears in lines of anime or game characters. To overcome this challenge, we propose segmenting lines of Japanese anime or game characters using subword units that were proposed mainly for deep learning, and extracting frequently occurring strings to obtain expressions that characterize their utterances. We analyzed the subword units weighted by TF/IDF according to gender, age, and each anime character and show that they are linguistic speech patterns that are specific for each feature. Additionally, a classification experiment shows that the model with subword units outperformed that with the conventional method.


Pattern extraction, Characterization of fictional characters, Subword units, Linguistic speech patterns, word segmentation.