Emotion and Meaning in Music

We have so various types of entertainment, and music is one of the most popular one. In this paper, we proposed music recommendation system that interactively adapts a user's personal affection with only a simple operation, in which both acoustic and meta features are used. The more a user uses the proposed system, the better the system adapts the user's personal affection and recommends the suitable songs. Through the evaluational experiment, we confirmed that the proposed system could recommend songs adapting user's personal affection even if the personal affection variated.

/pdf/interactive-music-recommendation-system-for-adapting-1r2qypfug1.pdf

Interactive music recommendation system for adapting personal affection: IMRAPA

/pdf/study-of-music-effects-on-human-factors-and-its-application-53wmwv43g6.pdf

Study of Music Effects on Human Factors and Its Application

A photograph is considered a medium with emotional legibility and a means of expressing and exchanging emotional experience. This research presents the interactive emotional photo frame system focusing on mediating individual affective experience among close relationships. This emotional photo frame system dynamically controls the photograph based on a user's affective states and user-specified emotion reaction rules. It is designed for helping users recognize and experience the same emotions with others. The system consists of an emotion recognition system, an emotion share server and an emotional digital picture frame. The emotion recognition system analyzes photoplethysmography, skin temperature and galvanic skin response signals to recognize user's emotional states and transmits the results to the server in real-time. The server stores user emotional data with individual emotion reaction rules that define how the picture frame should affect the photo in response to individual affective states. The emotional picture frame renders personalized visual and aural elements on the photograph according to the feedback of emotions. This paper presents an empirical exploration of the effectiveness of this system. The results revealed that most participants were influenced by their partner's emotion presented in this system. There was a strong relation of emotion sharing between the partners.

Mediating individual affective experience through the emotional photo frame

Existing music recommendation systems don't suit user subjectivity and are not naturally intuitive. We previously proposed a music recommendation system to address these problems. Our music recommendation system uses Kansei agents and a Kansei retrieval system. The Kansei agents employ a Kansei model and are characterized by a three-layered neural network. Music fluctuation properties are defined as inputs to the neural networks of the Kansei agents. Our previously proposed system returns recommendations based on user subjectivity. However, this system incurs significant user evaluation load. In this study, we introduce a distributed genetic algorithm (DGA) as an optimization method to address this problem. We compare the proposed DGA method to our previous method by simulation. The simulation results indicate that the proposed DGA method significantly outperforms previous method.

Music Recommendation System Improvement Using Distributed Genetic Algorithm

We studied the relationships between the acoustic fluctuation properties of music and the emotional evaluations of music as a component technology for an automated song selecting system based on instinct and human emotion. When people listen to music, they select songs reflect their own feelings at the time, and then they emotionally evaluate the song. We believe that our emotional evaluation of songs are influenced by the fluctuation properties of both the volume and pitch of songs. Thus, we focused on the fluctuation properties containing dynamic ideas concerning music, and extracted thirty six fluctuation properties concerning both the volume and pitch from each song using the Fast Fourier Transform. We also prepared a subjective evaluation experiment for plural songs using the Semantic Differential method, and obtained an emotional evaluation of the songs. Then, we studied the relationships between the extracted properties and the emotional evaluations of the songs by conducting a multiple discriminant analysis. As a result, a high percentage of the questions were answered correctly and low discriminant errors were shown, and therefore, we suggested that the fluctuation properties of the songs influenced the emotional evaluations of them. Furthermore, we confirmed the especial properties related with the emotional evaluation of the music by taking into consideration the coefficients of the liner discriminants of the canonical variates that describe the discriminant spaces.

Relationships between emotional evaluation of music and acoustic fluctuation properties

Recently, we have a lot of musical pieces due to a large capacity of storage. However, it would be difficult to select the song with bibliographic data as the capacity of the music database increases. Therefore, we proposed an emotional song selection system. In this study, the Acoustic - Emotion model was composed by relating the acoustic fluctuation features that can explain the time variation of music with the emotional evaluations of music obtained through the subjective evaluation experiments. Based on the model, the emotional evaluations of music were calculated from their acoustic features. Using the proposed system, user can select the song with the adjective words and their degrees.

/pdf/automated-song-selection-system-complying-with-emotional-107haoofgj.pdf

Automated song selection system complying with emotional requests

This paper relates audio features based on fluctuation of music with sensibility evaluation about music as a component technology for an automatic song select system demanded on human sensibility evaluation. When people listen to music, they select a song considering both their own feelings at the time and sensibility evaluation about the song. We consider that sensibility evaluations of songs are influenced by the features based on fluctuation about both volume and pitch of the songs. Thus, we focus on features of fluctuation that contain a dynamic idea on music, and extract thirty six features of fluctuation about both volume and pitch from each songs using Fast Fourier Transform. On the other, we prepare a subjective experiment for plural songs using Semantic Differential method, and obtain the sensibility evaluation about each song. Then, we study the relationships between extracted features and sensibility evaluation about the songs with multiple discriminant analysis. As a result, high accurate discriminant hit-rates and low discriminant error are shown, therefore we suggest that audio features based on fluctuation of songs influence sensibility evaluation about the songs. Furthermore, we confirm the especial parameters related with sensibility evaluation about music while considering canonical variates which construct discriminant spaces.

A Method of Relating Sensibility Evaluation about Music with Acoustic Features Based on Fluctuation

Recently, we have so many songs due to a large capacity of storage, however it becomes difficult to select the song using bibliographic data. In this paper, we propose Kansei song selection system based on music fluctuation features which named YSSS. In this system, the acoustic fluctuation features that show time variations of music are extracted from each songs, and the Kansei evaluations of the song are obtained through the subjective evaluation experiments. Then the features and the evaluations are related to each other, and the estimation spaces for Kansei evaluations are constructed. Using this estimation spaces, the Kansei evaluations are labeled with the songs. We proposed two types of song selection method, Exactly-Matching and Tolerant-List which considers the tolerance of human instinct. Through the subjective evaluation experiment, we confirmed the correct song selection and the contentment with proposed system. Furthermore, we confirmed that proposed system with Tolerant-List method shows better usability.

Kansei Song Selection System Based on Music Fluctuation Features and Comparison of Song Selection Algorithm

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Papers

Relationships between emotional evaluation of music and acoustic fluctuation properties

Automated song selection system complying with emotional requests

A Method of Relating Sensibility Evaluation about Music with Acoustic Features Based on Fluctuation

Kansei Song Selection System Based on Music Fluctuation Features and Comparison of Song Selection Algorithm