In　this　work,　a　multiple　sound　source　localization　and　counting　method　based　on　a　relaxed　sparsity　of　speech　signal　is　presented.　A　soundfield　microphone　is　adopted　to　overcome　the　redundancy　and　complexity　of　microphone　array　in　this　paper.　After　establishing　an　effective　measure,　the　relaxed　sparsity　of　speech　signals　is　investigated.　According　to　this　relaxed　sparsity,　we　can　obtain　an　extensive　assumption　that　＂single-source＂　zones　always　exist　among　the　soundfield　microphone　signals,　which　is　validated　by　statistical　analysis.　Based　on　＂single-source＂　zone　detecting,　the　proposed　method　jointly　estimates　the　number　of　active　sources　and　their　corresponding　DOAs　by　applying　a　peak　searching　approach　to　the　normalized　histogram　of　estimated　DOA.　The　cross　distortions　caused　by　multiple　simultaneously　occurring　sources　are　solved　by　estimating　DOA　in　these　＂single-source＂　zones.　The　evaluations　reveal　that　the　proposed　method　achieves　a　higher　accuracy　of　DOA　estimation　and　source　counting　compared　with　the　existing　techniques.　Furthermore,　the　proposed　method　has　higher　efficiency　and　lower　complexity,　which　makes　it　suitable　for　real-time　applications.