Term Dictionary Automatic Extraction Algorithm based on BiLSTM
Fangting Liu · 2025
With the increasing importance of machine translation research in the era of artificial intelligence, which are widely used in translation practice, contrastive analysis, language learning and other fields. As a basic resource, terminology dictionary plays an important role in cross-language natural language processing. To solve the problems in the field of cross-language natural language processing, this paper takes parallel corpus as the basis, studies the automatic extraction algorithm of term dictionary based on BiLSTM, combines BiLSTM, HMM, Viterbi and T-test and other methods to build a mathematical model of automatic extraction of term dictionary based on parallel corpus. Solve key problems such as sentence alignment, part-of-speech tagging and Chinese word segmentation. Through simulation experiments, the BiLSTM algorithm model in this paper is compared with RNN, CRF, LSTM and other network algorithm models, and the superiority of BiLSTM algorithm model is verified.