This　study　aims　to　present　an　optimization-based　audio　watermarking　using　entropy-based　watermarking　technique　in　the　wavelet　domain.　In　general,　the　performance　of　a　watermarking　system　is　measured　in　terms　of　signal-to-noise　ratio　(SNR)　and　bit　error　rate　(BER).　However,　there　is　a　tradeoff　between　them　which　issues　a　challenge　in　the　field　of　the　watermarking.　To　overcome　this　challenge,　this　study　first　integrates　entropy-based　embedding　technique　and　SNR　into　an　optimization　problem.　Because　of　uncertain　service　environment　for　the　audio　media,　an　optimization　algorithm　with　less　hardware　requirement　is　required　to　solve　this　problem.　Since　both　performance　index　and　constraint　are　nonlinear,　the　compact　particle　swarm　optimization　(cPSO)　which　suits　for　embedded　system　can　do　this　well.　In　addition,　the　hidden　information　can　be　extracted　without　knowledge　of　the　original　audio.　In　the　experiments,　the　performance　of　the　proposed　method　is　tested　and　the　results　verify　the　better　SNR　and　the　strong　robustness　against　most　signal　processing　or　attacks.