Designing a Web Novel with ML-based Generative Sound
With electronic publication taking its place as the new forms of reading experience, researches combining electronic publications and audio-visualization have been conducted. Related researches have explained that music can help the viewer’s reading experience. However, web novel, the driving force for this new market of electronic publication, does not fully explore this new possibility. In this research, I introduce the new viewing platform design for web novel using machine-learning generated music. The platform is designed to provide the sound matched to the text using the text sentiment analysis technology. Once the text is on the new platform design, each sentence’s emotion is immediately analyzed with the machine learning technology and music is generated and provided on the needed spots, which enhances the reading experience on the mobile phone interface. I conducted comparative experiments with existing web novels with 30 users. The result of experiment was positive. Most of readers found that the text with the machine learning-based sounds on the new platform design was helpful and enhanced their reading experience. With the result, We can see the possibilities of various applications and amalgamations in machine-learning driven environment. This research only examines the viewer’s exposure and response to the new reading experience, however it can also inspire the content’s creators to explore the new forms and styles with the proactive application of machine-learning technology.
(in progress) Sanghyeob and Jusub Kim, Designing a Web Novel with ML-based Generative Sound