Like in many other research areas, deep learning (DL) is increasingly adopted in music
recommender systems (MRS). Deep neural networks are used in this area particularly for …

Much work is focused upon music genre recognition (MGR) from audio recordings, symbolic
data, and other modalities. While reviews have been written of some of this work before, no …

Towards improving the performance in various music information processing tasks, recent
studies exploit different modalities able to capture diverse aspects of music. Such modalities …

We present a novel approach for analysing and classifying lyrics, experimenting both with
ngram models and more sophisticated features that model different dimensions of a song …

Music genre classification, especially using lyrics alone, remains a challenging topic in
Music Information Retrieval. In this study we apply recurrent neural network models to …

Music is an expressive form of communication often used to convey emotion in scenarios
where" words are not enough". Part of this information lies in the musical composition where …

Abstract We employ Natural Language Processing techniques to analyse 377,808 English
song lyrics from the “Two Million Song Database” corpus, focusing on the expression of …

Purpose Genre classification of songs based on lyrics is a challenging task even for
humans, however, state-of-the-art natural language processing has recently offered …

The trend for listening to music online has greatly increased over the past decade due to the
number of online musical tracks. The large music databases of music libraries that are …

The customized recommendation framework for music should accurately represent private
tastes. To obtain tailored feedback for the needs of various viewers, it takes adjustments. To …