In this paper, we investigate the benefits of deep learning approaches for the development of personalized assistive technology solutions for users with dysarthria, a speech disorder that leads to low intelligibility of users’ speaking. It prevents these people from using automatic speech recognition (ASR) solutions on computers and mobile devices. In order to address these issue, our effort is to leverage convolutional neural networks toward a speaker dependent ASR software solution intended for users with dysarthria, which can be trained according to particular user’s needs and preferences.