This paper describes the development of a text-to-speech system for Assamese language, using Deep Neural Network (DNN). The system is trained with speech data, collected by a consortium, that is available free of cost for academic use. The DNN based method eliminates the need for a grapheme to phoneme conversion; rather, it synthesizes speech directly from the UTF-8 based Assamese script. The results of objective and subjective evaluations confirm that the Assamese speech synthesized using DNN approach is better than the ones synthesized using the traditional hidden Markov model based text-to-speech system. © 2019 IEEE.