Understanding Differences Between Human Language Processing and Natural Language Processing by the Synchronized Model
Those authors contributed equally.
- DOI
- 10.2991/assehr.k.220131.052How to use a DOI?
- Keywords
- Natural Language Processing; Human Language Processing; Artificial Intelligence; Linguistics
- Abstract
Chat applications using Artificial Intelligence (AI) based on Natural Language Processing (NLP) platforms have been reported to be gradually accepted by people. This research aims to investigate differences between human language processing and Natural Language Processing (NLP) system, which is the core technology of most chat applications, using the synchronized language model. To achieve this objective, this research first distribute and collect questionnaires with questions such as the frequency and motivation of using AI chatbots among university students. The study then evaluate the selected chatbot with linguistic method and knowledge through semantics and pragmatics. Practically, this study proposes valid approaches to perfect existing chatbots. This study suggests that AI chatbots based on NLP can be applied to complete tasks but differ apparently from the human language processing system. The conclusion drawn from this study is that if the AI chatbot is developed to recognize misspelled words and their vocabulary is expanded, it will enhance the applicability of AI chatbots and fit them into people’s lives.
- Copyright
- © 2022 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Yixin Wang AU - Shisen Yue AU - Yanyi Zhong PY - 2022 DA - 2022/02/01 TI - Understanding Differences Between Human Language Processing and Natural Language Processing by the Synchronized Model BT - Proceedings of the 2021 International Conference on Education, Language and Art (ICELA 2021) PB - Atlantis Press SP - 287 EP - 294 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.220131.052 DO - 10.2991/assehr.k.220131.052 ID - Wang2022 ER -