Several studies have shown that music can reduce unpleasant emotions. Based on the results of this research, several systems have been proposed to suggest songs that match the emotions of the audience. As a part of the system, we aim to develop a method that can infer the emotional value of a song from its Japanese lyrics with higher accuracy, by applying the technology of inferring the emotions expressed in sentences. In addition to matching with a basic emotion dictionary, we use a Web search engine to evaluate the sentiment of words that are not included in the dictionary. As a further improvement, as a pre-processing of the input to the system, the system corrects the omissions of the following verbs or particles and inverted sentences, which are frequently used in Japanese lyrics, into normal sentences. We quantitatively evaluate the degree to which these processes improve the emotion estimation system. The results show that the preprocessing could improve the accuracy by about 4%. Japanese lyrics contain many informal sentences such as inversions. We pre-processed these sentences into formal sentences and investigated the effect of the pre-processing on the emotional inference of the lyrics. The results show that the preprocessing may improve the accuracy of emotion estimation.
Keywords: Japanese song lyrics; emotion tagging; mood management; search engine.