The　development　of　generative　artificial　intelligence　(AI)　has　demonstrated　notable　advancements　in　the　domain　of　music　synthesis.　However,　a　perceived　lack　of　creativity　in　the　generated　content　has　drawn　significant　attention　from　the　public.　To　address　this,　this　paper　introduces　a　novel　approach　to　personalized　music　synthesis,　incorporating　a　human-in-the-loop　generation.　This　method　leverages　the　dual　strengths　of　interactive　evolutionary　computation,　known　for　its　capturing　user　preferences,　and　generative　adversarial　network,　renowned　for　its　capacity　to　autonomously　produce　high-quality　music.　The　primary　objective　of　this　integration　is　to　augment　the　credibility　and　diversity　of　generative　AI　in　music　synthesis,　fostering　computational　artistic　creativity　in　humans.　Furthermore,　a　user-friendly　interactive　music　player　has　been　designed　to　facilitate　users　in　the　music　synthesis　process.　The　proposed　method　exemplifies　a　paradigm　wherein　users　manipulate　latent　space　through　human-machine　interaction,　underscoring　the　pivotal　role　of　humans　in　the　synthesis　of　diverse　and　creative　music.　©　2024　Copyright　is　held　by　the　owner/author(s).　Publication　rights　licensed　to　ACM.