Task: Language Identification
Input (Spanish, English): This paper is motivated by the ability that human's visual system can recognize contents of environment by from critical features, and tried to investigate whether neural networks can also have this kind of ability.  Specifically, the paper proposed to use Auto-Encoder (AE) as the network to reconstruct the low fidelity of visual input. Moreover, similar to Mnih et al. (2014),  the paper also proposed to use a recurrent fashion to mimic the sequential behavior the  human visual system.   I think the paper is well motivated. However, there are several concerns: 1. The baselines of the paper are too weak. Nearest neighbor, bilinear, bicubic and cubic interpolations without any learning procedure are of course performed worse than AE based models. The author should compare with the STOA methods such as
Output (English): en