CriticAI's innovative multimodal analysis architecture combines audio and text processing in depth. When the user provides lyrics, the system uses the BERT model to extract semantic features, analyze metrics such as rhyme density (number of rhymes per 100 words), emotional polarity (ratio of positive/negative emotions) and narrative coherence, and cross-validate with melodic emotions. Tests showed that the analysis report with lyrics could more accurately identify flow changes in Rap songs (detection sensitivity increased by 37%) and emotional climax passages in lyrical songs. A singer-songwriter utilized this feature to identify the problem of emotional conflict between chorus lyrics and chord progressions, and after the modification, the work's emotional conveyance score in the listener test improved from 6.2 to 8.5.
This answer comes from the articleCriticAI: AI-powered music quality analysis toolThe
