In　this　paper,　we　propose　a　new　voice　activity　detection　(VAD)　algorithm　to　improve　the　speech　detection　robustness　in　nonstationary　noisy　environments.　At　front-end,　Wiener　filtering　speech　enhancement　is　adopted　to　suppress　noise　from　noisy　speech.　Then,　at　back-end,　the　voice　activity　detector　based　on　mel　filter-bank　spectral　entropy　is　presented　to　distinguish　speech　from　noise.　We　have　evaluated　system　performance　under　noisy　environments.　Experimental　results　indicate　that　the　proposed　method　is　useful　for　achieving　a　considerable　performance　improvement　for　the　VAD　in　nonstationary　noise.