We incorporate charn-MS-vec, which is an embedding constructed from character n-gram embeddings, into RNN language models since, as discussed earlier, previous studies revealed that we can construct better word embeddings by using character n-gram embeddings<cite> (Wieting et al. 2016</cite>; Bojanowski et al. 2017 ).