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Register a new userMulti-Emotion Classification for Song Lyrics
التصنيف متعدد العاطفة للحصول على كلمات الأغاني
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كلمات الأغاني تنقل العديد من المشاعر إلى المستمع وصور بقوة الحالة العاطفية للكاتب أو المغني.يفحص هذه الورقة مجموعة متنوعة من نهج النمذجة لمشكلة تصنيف متعددة العاطفة للأغاني.نقدم DataSet DataSet Edmonds DataSet، وهي كلمات بيانات كلمات مشفخة عن العاطفة من منظور القارئ، وتعليق DataSet of Mihalcea و Stripparava (2012) على مستوى الأغنية.نجد أن النماذج المدربة على مجموعات بيانات الأغنية الصغيرة نسبيا تحقق أداء أفضل بشكل هامشي من بيرت (ديفلين وآخرون)
Song lyrics convey a multitude of emotions to the listener and powerfully portray the emotional state of the writer or singer. This paper examines a variety of modeling approaches to the multi-emotion classification problem for songs. We introduce the Edmonds Dance dataset, a novel emotion-annotated lyrics dataset from the reader's perspective, and annotate the dataset of Mihalcea and Strapparava (2012) at the song level. We find that models trained on relatively small song datasets achieve marginally better performance than BERT (Devlin et al., 2018) fine-tuned on large social media or dialog datasets.
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