Preserving　audio　scenes　in　the　form　of　audio　objects　has　become　common　in　recent　years.　Object-based　audio　techniques　provide　more　flexibility　for　personalized　rendering　as　well　as　a　more　accurate　audio　object　trajectory.　For　encoding　and　transmitting　multiple　audio　objects　in　a　lossy　manner,　a　new　compression　framework　for　multiple　simultaneously　occurring　audio　objects　is　presented　in　this　work.　The　proposed　encoding　approach　is　based　on　the　intra-object　sparsity　(approximate　k-sparsity).　After　establishing　a　quantitative　measure　of　approximate　k-sparsity,　statistical　analysis　is　employed　to　validate　the　proposed　intra-object　sparsity　of　audio　objects.　By　exploring　this　intra-object　sparsity,　multiple　simultaneously　occurring　audio　objects　are　compressed　into　a　mono　downmix　signal　with　side　information.　This　downmix　signal　can　be　further　compressed　by　legacy　audio　codecs.　Meanwhile,　the　side　information　is　transmitted　in　a　lossless　manner.　The　objective　and　subjective　evaluations　revealed　that　the　proposed　compression　framework　achieved　better　perceptual　quality　compared　to　an　existing　technique　where　up　to　eight　audio　objects　are　considered.　The　subjective　evaluations　also　confirmed　that　the　proposed　approach　is　able　to　achieve　scalable　transmission　according　to　the　bandwidth　while　preserving　the　perceptual　quality　of　both　the　individual　audio　objects　and　the　spatial　audio　scenes.