title: Memory Augmented Lookup Dictionary Based Language Modeling for Automatic Speech Recognition
abstract: Recent studies have shown that using an external Language Model (LM) benefits the end-to-end Automatic Speech Recognition (ASR).However, predicting tokens that appear less frequently in the training set is still quite challenging.The longtail prediction problems have been widely studied in many applications, but only been addressed by a few studies for ASR and LMs.In this paper, we propose a new memory augmented lookup dictionary based Transformer architecture for LM.The newly introduced lookup 