Implicit Perception of Differences between NLP-Produced and Human-Produced Language in the Mentalizing Network.

ABSTRACT: Natural language processing (NLP) is central to the communication with machines and among ourselves, and NLP research field has long sought to produce human-quality language. Identification of informative criteria for measuring NLP-produced language quality will support development of ever-better NLP tools. The authors hypothesize that mentalizing network neural activity may be used to distinguish NLP-produced language from human-produced language, even for cases where human judges cannot subjectively distinguish the language source. Using the social chatbots Google Meena in English and Microsoft XiaoIce in Chinese to generate NLP-produced language, behavioral tests which reveal that variance of personality perceived from chatbot chats is larger than for human chats are conducted, suggesti

SUBMITTER: Wei Z 

PROVIDER: S-EPMC10131862 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature