 This paper proposes a novel deep learning architecture that uses raw brainwave data to detect speech. This approach is more efficient than traditional methods which require extensive pre-processing of the data. Additionally, it is able to provide explanations for its results, making it suitable for use in real-time applications. This article was authored by Morgan Stewart, Sir John Lasagia, Jerry J. Shee and others.