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Joint sentiment analysis of lyrics and audio in music

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arxiv 2405.01988 v1 pith:AZN4XVLK submitted 2024-05-03 cs.SD cs.AIcs.CLcs.LGeess.AS

classification cs.SDcs.AIcs.CLcs.LGeess.AS
keywords audiolyricssentimentanalysisapproachescausesdatamusic
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Sentiment or mood can express themselves on various levels in music. In automatic analysis, the actual audio data is usually analyzed, but the lyrics can also play a crucial role in the perception of moods. We first evaluate various models for sentiment analysis based on lyrics and audio separately. The corresponding approaches already show satisfactory results, but they also exhibit weaknesses, the causes of which we examine in more detail. Furthermore, different approaches to combining the audio and lyrics results are proposed and evaluated. Considering both modalities generally leads to improved performance. We investigate misclassifications and (also intentional) contradictions between audio and lyrics sentiment more closely, and identify possible causes. Finally, we address fundamental problems in this research area, such as high subjectivity, lack of data, and inconsistency in emotion taxonomies.

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Cited by 1 Pith paper

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  1. Content filtering methods for music recommendation: A review

    cs.IR 2025-07 conditional

    A survey of content-based music recommendation methods, including audio analysis, lyrics analysis, and context awareness, with no new experimental results.

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