This study aims to grasp the regional differences in the musical characteristics inherent in the traditional Japanese folk songs by extracting and comparing the characteristics of each area by conducting quantitative analysis in order to promote digital humanities research on traditional Japanese folk songs.
In the previous studies, We have sampled 1,794 song pieces from 45 Japanese prefectures, and have clarified the following three points by extracting and comparing their respective musical patterns (Kawase and Tokosumi 2011): (1) the most important characteristics in the melody of Japanese folk songs is the transition pattern, which is based on an interval of perfect fourth pitch; (2) regionally adjacent areas tend to have similar musical characteristics; and (3) the differences in the musical characteristics almost match the East-West division in the geolinguistics or in the folkloristics from a broader perspective. However, to conduct more detailed analysis in order to empirically clarify the structures by which music has spread and changed in traditional settlements, it is necessary to expand the data and do comparisons based on the old Japanese provinces (ancient administrative units that were used under the ritsuryo system before the modern prefecture system was established).
In this study, we analyzed all the songs listed from the Shikoku district (literally meaning four provinces, located south of Honshu and east of Kyushu district) in order to build a digital analysis platform for all the songs recorded in the Nihon Min’yo Taikan (Anthology of Japanese Folk Songs) and execute quantitative comparisons of musical characteristics between neighboring regions (Kawase 2016a; 2016b).
Specifically, the procedures are as follows: (1) we digitized all the songs from the Shikoku district and generated sequences that contain interval information from the song melodies; (2) extracted patterns that appear with high frequency in the generated sequences; and (3) summarized the musical characteristics of the folk songs from the Shikoku district by comparing the patterns between provinces using statistical techniques.
In order to digitize the Japanese folk song pieces, we generate a sequence of notes by converting the music score into MusicXML file format. We devised a method of digitizing each note in terms of its relative pitch by subtracting the next pitch height for a given MusicXML. It is possible to generate a sequence T that carries information about the pitch to the next note: T = (t1, t2, … , ti, …, tn). An example of the corresponding pitch intervals for ti can be written as shown in Table 1. We treat sequence T as a categorical time series, and execute N-gram analysis by conducting unigram, bigram, and trigram patterns to clarify major transitions and their trends in the Shikoku district.
Based on the results of N-gram analysis, we found that folk songs from the Shikoku district have a strong tendency to form melodic leaps followed by progressions back to the first sung note or perfect fourth intervals, as a characteristic of N=1, 2, 3 interval transition pattern. In particular, patterns where the total of the elements themselves for N=2 form perfect fourth intervals are the ascending and descending order for the four types of tetrachords that Fumio Koizumi proposed (Koizumi 1958). In addition, patterns that include N=3 tetrachords also were extracted remarkably often.
The tetrachord is a unit consisting of two stable outlining tones with the interval of a perfect fourth pitch, and one unstable intermediate tone located between them. Depending on the position of the intermediate tone, four different types of tetrachords can be formed (Table2). Below are some discussions about the features of folk songs, focusing on interval transitions that form tetrachords.
Out of four types, we found that min’yo tetrachords were used with an extremely high frequency, and the next highest was ritsu tetrachords. Furthermore, we conducted a cluster analysis (hierarchical clustering) based on the frequency of occurrences of the tetrachords to see the differences in each province (see Figure 1). When calculating distances between each element, we normalized the frequency that the tetrachords appear, and used the Euclidean distance and the algorithm from the Ward method.
Compared with our previous analysis on neighboring regions such as the Kyushu and Chugoku districts (Kawase 2015; 2016ab), we find that folk songs from the eastern two provinces (Sanuki and Awa) and western two provinces (Iyo and Tosa) of Shikoku district can be explained in terms of differences in melodic structures within tetrachords. In particular, for western provinces, there is a tendency to create the ritsu and ryukyu tetrachords, which also appear frequently in Kyushu district. In contrast, for eastern provinces, there is a tendency to create the miyakobushi tetrachord, which is thought to be originated from music of urban areas such as in Kyoto. Thus, the tetrachord turned out to be salient characteristic by which to classify the melodies of east and west regions of Shikoku district.
This work was mainly supported by the Japanese Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (15K21601) and the Suntory Foundation Research Grants for Young Scholars.
 Kawase, A. (2016a) Regional classification of traditional Japanese folk songs from the Chugoku district, In Proceedings of the Digital Humanities 2016: DH2016 (in press).
 Kawase, A. (2016b) Extracting the musical schemas of traditional Japanese folk songs from Kyushu district, In Proceedings of the 14th International Conference for Music Perception and Cognition: ICMPC14 (in press).
 Kawase, A. and Tokosumi, A. (2011) Regional classification of traditional Japanese folk songs, International Journal of Affective Engineering 10 (1): 19-27.
 Koizumi, F. (1958) Nihon dento ongaku no kenkyu (Studies on Traditional Music of Japan 1), Ongaku no tomosha.
 Nihon Hoso Kyokai (1944-1993) Nihon Min’yo Taikan (Anthology of Japanese Folk Songs), Nihon Hoso Kyokai Shuppan.
 MusicXML http://www.musicxml.com/for-developers/ [accessed 15 May 2016].