Turkish Music Genre Classification using Audio and Lyrics Features

Abstract

Music Information Retrieval (MIR) has become a popular research area in recent years. In this context, researchers have developed music information systems to find solutions for such major problems as automatic playlist creation, hit song detection, and music genre or mood classification. Meta-data information, lyrics, or melodic content of music are used as feature resource in previous works. However, lyrics do not often used in MIR systems and the number of works in this field is not enough especially for Turkish. In this paper, firstly, we have extended our previously created Turkish MIR (TMIR) dataset, which comprises of Turkish lyrics, by including the audio file of each song. Secondly, we have investigated the effect of using audio and textual features together or separately on automatic Music Genre Classification (MGC). We have extracted textual features from lyrics using different feature extraction models such as word2vec and traditional Bag of Words. We have conducted our experiments on Support Vector Machine (SVM) algorithm and analysed the impact of feature selection and different feature groups on MGC. We have considered lyrics based MGC as a text classification task and also investigated the effect of term weighting method. Experimental results show that textual features can also be effective as well as audio features for Turkish MGC, especially when a supervised term weighting method is employed. We have achieved the highest success rate as 99,12% by using both audio and textual features together.

Derin Öğrenme İle Türkçe Müziklerden Müzik Türü Sınıflandırması

“…Analiz aşamasında, son zamanlarda yapay zekâ teknolojilerinin sinyal işleme ile birlikte kullanılmasıyla birlikte müzik ile ilgili akademik alanda da birçok çalışma yapıldığı görülmektedir. Bu çalışmaların çoğu; müziğin akustik analizi, makam tanıma, müzik türü sınıflandırma ve müzikten duygu tanıma gibi çalışmaları içermektedir (Abidin ve ark., 2017;Çoban, 2017;Er ve Çiğ, 2020).…”

Lukthung Classification Using Neural Networks on Lyrics and Audios

“…Recently, both lyrics and audios have been incorporated into classifiers together [8], [9]. The assumption is that lyrics contain inherent semantics that cannot be captured by audios.…”