A method for training an artificial neural network-based speech recognition model is disclosed. In the method for training an artificial neural network-based speech recognition model, a user's speech is learned by using target data representing features and non-target data representing non-features as random inputs and outputs, and then the user's speech is recognized under a noise situation. A method for training an artificial neural network-based speech recognition model and speech recognition device of the present disclosure can be associated with artificial intelligence modules, drones (unmanned aerial vehicles (UAVs)), robots, augmented reality (AR) devices, virtual reality (VR) devices, devices related to 5G service, etc.