We present a novel method to detect when a person is speaking using respiratory measurements collected in the natural environment. A speaker's respiration pattern is sampled from a respiratory inductive plethysmograph (RIP) band worn around the speaker's chest. Ratio of inhalation duration to exhalation duration (IE ratio) has traditionally been used to detect speaking in controlled lab environment . However, we find that IE ratio is inadequate in the natural environment. We propose several new features to be used along with IE ratio. Using various statistics over these features, we obtain >95% accuracy in classifying respiration measurements into "speaking" or "silence" states with 10-fold cross validation. Our demonstration will show realtime capture of the respiration signal, computation of features, and detection of speaking and silence, all on a mobile smartphone.