What is it about?
The digitization of intangible cultural heritage has given rise to new needs but also great opportunities for the preservation, analysis, education and propagation of cultural items that often constitute vast data bases of sophisticated works of art. This is particular the case of songs that comprise a combination of lyrics and music, each constituting an important domain of art. The preservation and propagation of this kind of art around the world becomes yet harder by taking into account the different languages that this art was originally created in, e.g. English, French, Portuguese Greek, Ancient Greek etc. The aim of this specific research is to develop a software tool that will support computer-aided functions of musical and lyrical analysis. The provision of these particular functions is realized through the integration in the proposed software tool of advanced natural language processing algorithms, text mining and thematic modeling. Therefore, it is an application that proposes the utilization of innovative computational methods of the broader object of Machine Learning and Pattern Recognition for the automated processing, clustering and semantic analysis of textual information. As a case of observation, the automated analysis of a part of the poetic activity of a Greek lyrics-writer is presented with the ultimate goal of promoting the cultural heritage.
Featured Image
Photo by Kati Hoehl on Unsplash
Why is it important?
The research paper aims to develop an innovative software tool that provides automated musicological and lyrical analysis services. The tool is named MUSILYAS (MUSIc Lyrics Analysis of Songs). In fact, the computer assistance of the aforementioned functions is based on the implementation, modification and extension of machine learning algorithms that focus on natural language processing, text mining and data clustering by incorporating semantic criteria. The possible users of MUSILYAS, span a great variety of related specialties including: i. Musicologists ii. Musicians iii. Lyrics-writers iv. Composers v. Instructors/Tutors/Teachers vi. Learners vii. Music Fans viii. Culture tourists The software tool presented here confronts the problem of semantic modeling on lyrics collections focusing on the automation of the following processes: i. Storage and retrieval of lyrics collections. ii. Processing of the textual information. iii. Mining the central thematic / semantic axes that rule a given structure of lyrics. iv. Organization of the structure of lyrics into thematic/semantic axes that have been recognized. v. Lyrics sorting based on the recognized thematic/semantic axes.
Perspectives
This research paper presented MUSILYAN, a platform for synthesizing textual information analysis algorithms with special emphasis on the management and labeling of semantic content. The ability to thematically organize a body of lyrics, including the time dimension, makes the potential applications of the presented software tool almost inexhaustible. Future extensions could be related to the automated analysis of the musical (audio) content of an artist’s work. The integration of multiple forms of information in the software tool will in turn highlight the need for joint study of the work of lyrics writers, composers and musicians. In any case, this is an attempt to synthesize individual cognitive objects with the ultimate goal of analyzing and promoting the cultural heritage of a specific country.
Prof.-Dr. George A. Tsihrintzis
University of Pireaus
Read the Original
This page is a summary of: Machine Learning in Intangible Cultural Analytics: The Case of Greek Songs’ Lyrics, November 2021, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/ictai52525.2021.00050.
You can read the full text:
Contributors
The following have contributed to this page
