Analysis of Intelligent English Chunk Recognition based on Knowledge Corpus

Abstract

Chunks play an important role in applied linguistics, such as Teaching English as a Second Language (TESL) and Computer-Aided Translation (CAT). Although corpora have already been widely used in the areas mentioned above, annotation and recognition of chunks are mainly done manually. Computer- and linguistic-based chunk recognition is significant in natural language processing (NLP). This paper briefly introduced the intelligent recognition of English chunks and applied the Recurrent Neural Network (RNN) to recognise chunks. To strengthen the RNN, it was improved by Long Short Term Memory (LSTM) for recognising English chunk. The LSTM-RNN was compared with support vector machine (SVM) and RNN in simulation experiments. The results suggested that the performance of the LSTM-RNN was always the highest when dealing with English texts, no matter whether it was trained using a general corpus or a corpus of specialised domain knowledge.