  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.
