Abstract:

Traditional methods of terminology management in interpreting have some problems, including information isolated island, real-time insufficiency, low efficiency, and intelligence insufficiency. Thanks to the powerful text processing capabilities, large language models (LLMs) offer new opportunities for terminology management in interpreting. LLMs can automatically extract terms, provide term translations, analyze term usage, thus improving translation quality, increasing management efficiency, and supporting the professional development of interpreters. However, the application of LLMs in terminology management for interpreting still faces challenges such as bias in training data, concerns over data privacy and security, and high costs for training an maintenance. Future research should further explore the application scenarios of LLMs in terminology management for interpreting, optimize algorithms and models to improve accuracy and reliability, and develop more user-friendly and intelligent terminology management tools.

Key words: interpreting, terminology management, large language models, artificial intelligence