Emotions Detection in Music Lyrics
Using Machine Learning and Keyword-Based Approaches
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Search of music through emotions is one of the main criteria utilized by users on Internet. Real-world music databases from sites like AllMusic or Last.fm grow larger and larger on a daily basis, which requires a tremendous amount of manual work for keeping them updated. As manual annotation with emotion tags is an expensive time-consuming task, we need automatic Music Emotion Recognition systems (MER). This book is focused on the task of automatic detection of emotions in music lyrics and in the importance of the different music dimensions (e.g., audio, lyrics) for the task of detection of em...
Search of music through emotions is one of the main criteria utilized by users on Internet. Real-world music databases from sites like AllMusic or Last.fm grow larger and larger on a daily basis, which requires a tremendous amount of manual work for keeping them updated. As manual annotation with emotion tags is an expensive time-consuming task, we need automatic Music Emotion Recognition systems (MER). This book is focused on the task of automatic detection of emotions in music lyrics and in the importance of the different music dimensions (e.g., audio, lyrics) for the task of detection of emotions in music. In this book, different emotion detection approaches are analyzed and a new system is proposed. Topics such as relation between music features and emotions and music emotion variation detection are covered, as well as, identification of the most important music features to each emotion. This analysis contributes to unify the current efforts in this area. It should be particularly useful to researchers working in MER in general and in detection of emotions in music lyrics or general text in particular and as support to (under)graduate courses related to these topics.
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