Communication is essential feature in human communities. For some reasons, deaf-mute disabled people lose their ability to hear, speak, or both which makes them suffer to communicate and convey their ideas, especially with normal people. Sign language is the solution for communication in the deaf-mute societies, but it is difficult for the rest of people to understand. Therefore, in this work, a cost effective Deaf-Mute Electronic Assistant System (DMEAS) has been developed to help in solving the communication problem between the deaf-mute people and the normal people. The system hardware consists only of a Myo armband from \textit{Thalmic Labs} and a smartphone. The Myo armband reads the electromyographic signals of the muscles of the disabled person's forearm through non-invasive, surface mounted electrodes (sEMG) and sends the data directly to the smartphone via Bluetooth. The smartphone will recognize and interpret them to a predefined word depending on the hand gestures. The recognized gesture will be displayed on the smartphone screen as well as displaying the text of the word related to the gesture and its voice record. All the EMG signals are processed using discrete wavelet transform and classified by neural network classifier. The system was extensively tested through experiments by normal subjects to prove its functionality.