Naoko Kosugi

Extraction and visualization of the repetitive structure of music in acoustic data: misual project

This paper proposes a method to identify and visualize repetitive structures in music in PCM format using a similarity matrix. The Hough transform is used on the matrix to identify repetitions in a tune. Identified structures are visualized on an image called misual. Misual is a colored cylinder of a varying diameter, where colors represent repetitions and the diameter represents volume changes. The performance of the identification and visualization is evaluated with well-known classical tunes. Misual shows not only the dominant repetitions but also repeated patterns which can not be easily recognized while listening to a tune or reading its score. By revealing these patterns, misual gives a new point of view for musical structure analysis and at the same time gives people a new way to appreciate music.

Misual: music visualization based on acoustic data

This paper describes a music visualization method called Misual. The goal of this research to provide objective and static information regarding musical impressions that will enable people to efficiently categorize a huge number of music pieces and select favorites from them. Features are directly extracted from music and then visualized in an image that suits human intuition. As a first step in this research, volume transitions and repetitions are focued on as the visualized objects. For the volume transition, power information is extracted and then smoothed by a moving average. This information is continuously visualized with 3D-like images, in which radii of circles reflect the volume information. Repetitions are visualized with color. These are detected on the basis of the frame-to-frame similarity measured by the Mel-frequency cepstrum. These two kinds of information were visualized for three pieces of real music. The visualizations will be useful for roughly grasping the musical features in a very short time and imagining the music intuitively.

Time-dependent genre recognition by means of instantaneous frequency spectrum based on Hilbert-Huang transform

This paper describes a new method of music genre recognition. Even for people it is difficult to define musical genres, because a genre is something more than a set of rules. Automation of this task could improve the work of multiple audio-related WEB portals, such as audio-libraries, and could simplify human activity in other music-related areas. For music genre recognition, we introduce the instantaneous frequency spectrum (IFS) whose calculation is based on the Hilbert-Huang transform. In our method, IFSs of audio signals are generated from their instantaneous frequencies and used to calculate music genre templates. The experimental results for three test music pieces show that the method can accurately detect and differentiate genres of tunes. Slicing test music into frames and recognizing genres for short fragments of a whole music piece gives a precise description of a pieces internal structure, which could help to enhance peoples understanding of the music. Presentation of this information also is an advance in music visualization.

Ninchisho Chienowa-net: a website to share good dementia care techniques

This paper presents our web system to collect and publish good dementia care techniques for caregivers. The system collects a lot of dementia care information from caregivers and, in the future, it will extract good dementia care methods from the information by using the text mining technology. The web system was released for about 40 users in July, 2015 to validate the system functions and to get feedbacks for the system. The system was well received by the users. We also found that the caregivers spend about 20 minutes on average for inputting care information in a single session. In addition, the number of input data of the choice was almost double of those of the blank input. We will improve the web system based on these results and the feedbacks from the users in the future.

Music Retrieval and Adjustment Technique to Support and Motivate Ergotherapy and Daily Exercises

To maintain and uplift the motivation for doing exercise which is tend to be too simple in rehabilitation and ergotherapy, doing exercise with music is one of the good solutions. In this paper, we confirm that doing exercise with music is fun. Next, we design five types of musical features which relate to exercises. These features are evaluated by doing five types of exercises with listening to the tunes. Based on the results obtained from the experiments, we found many new things, for example, tempo has the adjustment limitation based on how well the user knows the tune. In this paper, we report the latest results from the experiments and explain the way to progress of this research.

A Prototype System of Remote Music Therapy Using the Latest Communication Technology in Japan

This paper describes a prototype system of remote music therapy for elderly people with dementia using the latest communication technology in Japan. The system uses the latest high-speed optical network, called NGN (Next Generation Network) and the latest terminal especially for audio data communication called Hikari DUETTO NY1, which was released at the end of the last year. We did an experiment of the system using the real communication environment in this January between Tokyo and Osaka. The communication time of the system between Tokyo and Osaka was about 25.5 msec. Thus, we confirmed that the system was able to provide almost real-time audio data communication. Based on the result, the feasibility of music therapy activities, such as singing and exercises with music, using the system was examined. We confirmed that the singing activity which is the most important one in the music therapy was feasible.