Character n-gram Embeddings to Improve RNN Language Models
Table 4: Perplexities on the PTB dataset where an input word is infrequent in the training data, which means its frequency is lower than 2,000.
['Method', 'Valid', 'Test']
This table indicates that the proposed method can improve the performance even if an input word is infrequent. In other words, charn-MS-vec helps represent the meanings of infrequent words. Therefore, we answer yes to the second research question in the case of our experimental settings.