Recent technique advances have made sensor nodes to be smaller, cheaper and more powerful. Compared with traditional centralized sensing systems, wireless sensor networks are very easy to deploy and can be deployed densely. They have a better sensing coverage and provide more reliable information delivery. Those advantages make wireless sensor networks very useful in a wide variety of applications. As one of active research areas, acoustic monitoring with wireless sensor networks is still new, and very few applications can recognize human voice, discriminate human speech and music, or identify individual speakers. In this thesis work, we designed and implemented an acoustic monitoring system with a wireless sensor network to classify human voice versus music. We also introduce a new, effective sound source localization method, using Root Mean Square (RMS) detected by different nodes of a wireless sensor network to estimate the speaker's location. The experimental results show that our approaches are effective. This research could form a basis for further developing speech recognition, speaker identification, even emotion detection with wireless sensor networks.