Although traditional AES methods typically rely on handcrafted features (Larkey, 1998; Foltz et al., 1999; Attali and Burstein, 2006; Dikli, 2006; Wang and Brown, 2008; Chen and He, 2013; Somasundaran et al., 2014; Yannakoudakis et al., 2014; <cite>Phandi et al., 2015</cite>) , recent results indicate that state-of-the-art deep learning methods reach better performance (Alikaniotis et al., 2016; Dong and Zhang, 2016; Taghipour and Ng, 2016; Song et al., 2017; Tay et al., 2018) , perhaps because these methods are able to capture subtle and complex information that is relevant to the task (Dong and Zhang, 2016) .