There has been an increased interest in multimodal language processing including multimodal dialog, question answering, sentiment analysis, and speech recognition.
recently, neural models such as cascaded residual autoencoders (Tran et al., 2017), deep adversarial learning (Cai et al., 2018), or translation-based learning (Pham et al., 2019) have also been proposed.