Music can evoke various emotions, and with the advancement of technology, it
has become more accessible to people. Bangla music, which portrays different
human emotions, lacks sufficient research. The authors of this article aim to
analyze Bangla songs and classify their moods based on the lyrics. To achieve
this, this research has compiled a dataset of 4000 Bangla song lyrics, genres,
and used Natural Language Processing and the Bert Algorithm to analyze the
data. Among the 4000 songs, 1513 songs are represented for the sad mood, 1362
for the romantic mood, 886 for happiness, and the rest 239 are classified as
relaxation. By embedding the lyrics of the songs, the authors have classified
the songs into four moods: Happy, Sad, Romantic, and Relaxed. This research is
crucial as it enables a multi-class classification of songs' moods, making the
music more relatable to people's emotions. The article presents the automated
result of the four moods accurately derived from the song lyrics.

本研究使用自然语言处理和 Bert 算法对 4000 首孟加拉歌曲的歌词进行分析，将其分为快乐、悲伤、浪漫和放松四种情绪，从而实现了歌曲情绪的多类分类，使音乐与人们的情感更加契合。