Open-Domain Name Error Detection using a Multi-Task RNN
Hao Cheng, Hao Fang, Mari Ostendorf · 2015
Out-of-vocabulary name errors in speech recognition create significant problems for downstream language processing, but the fact that they are rare poses challenges for automatic detection, particularly in an open-domain scenario.To address this problem, a multi-task recurrent neural network language model for sentence-level name detection is proposed for use in combination with out-of-vocabulary word detection.The sentence-level model is also effective for leveraging external text data.Experiments show a 26% improvement in name-error detection F-score over a system using n-gram lexical features.