Join "Hot Word Detection with Python, Neural Networks-TensorFlow and ROS Integration" on Robociti to upgrade your skills in Speech Processing and learn how to construct a hot word/wake-up word detection module that can process a live or pre-recorded audio stream in order to detect a preset hot word that can be used to wake up your system for further processing, much like in the case of many popular AI-based voice assistant systems that can be woken by a word, like "Hey Google", "Hey Alexa" or others. And do this by using popular frameworks like Python programming for audio processing, TensorFlow and Keras for Neural Network model construction and fast deployment, and ROS (Robot Operating System) for further integration in larger projects in AI and Robotics. Firstly, students are taught how to pre-process their audio input of the hot word in order to create their data set, including the recording and sampling of the audio and the Data Augmentation steps using Python commands. Then, the process for using the dataset constructed to train a suggested Neural Network Model based on TensorFlow and Keras is analyzed, along with tips about how to optimize the training process. Finally, TensorFlow Lite is used for fast deployment of our model on a scarce resource system and the module is integrated into the ROS framework for easier use with other modules in robotic and AI applications.