The relationship between music preferences with age is an interesting but rarely studied topic. The limited relevant research mostly concentrated on the musical genre level or a certain age group. In this thesis, we study the music preferences of different generations from an acoustic perspective, intending to understand the differences and trends in the various music tastes. We jointly took advantage of the LFM-1b dataset, MusicBrainz, and AcousticBrainz to collect the user’s listening events and acoustic information. F-test feature selection and support vector machines were then used to analyze the correlation between generations’ preferences and acoustic features. We finally found the most relevant acoustic features and revealed their trends along with the generation changing. For example, the younger listeners tend to listen to songs that are spectrally more complex, while the older listeners show more interest in “sad” music. We further interpreted these features, attempting to understand the reasons for these trends. Our findings suggested that some previously observed genre preferences of relevant work were associated with these acoustic features. Therefore, this thesis provides a new perspective for the study on music preferences and age.