Speech recognition with DNN-LAS

In this project, we build a speech recognition system by trying to improve the original Listen, Spell and Attend model. We evaluated our performance with two metrics: character error rate (CER) and word error rate (WER). We were able to generate a result only 3.8% below Google with only one twentieth of their data set.