Affiliation:
1. Yangzhou Polytechnic College, Jiangsu, Yangzhou 225009, China
Abstract
Artificial intelligence now plays a significant role in both daily life and scientific research because of the rapid advancement of this technology in recent years. Making full use of the phrases in the translation phrase table for translation is challenging since the phrase matching is too accurate when the translation machine decodes. Fully automatic machine translation struggles to meet the expectations of its users since there are more or less translation faults brought on by data bottlenecks. Therefore, we require collaborative assisted translation technology for human-computer interaction. This work strengthens the research on collaborative translation techniques and ways for monitoring the human-computer interaction environment in order to further improve translation quality. This essay investigates and discusses human-computer translation techniques as well as related ideas in collaborative translation and human-computer interaction. The translation similarity model is incorporated into the translation system model together with an overall qualitative knowledge and logical reasoning capability of human-computer interaction to offer fresh strategies and methods for collaborative translation between humans and computers. According to the experimental findings, the accuracy rate of the collaborative translation system for human-computer interaction based on artificial intelligence technology can achieve 98.2% and 95.6%. The quality of the translation is enhanced after human-computer interaction, and the editing gap between the incorrect and auxiliary translations is narrowed, demonstrating the efficiency of the system and demonstrating its viability. In order to enhance the accuracy of system translation and the effectiveness of system operation, it is important to investigate the collaborative translation mode of human-computer interaction based on artificial intelligence technology.
Funder
The General Project of Philosophy and Social Science Research for Colleges and Universities in Jiangsu Province
Subject
Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health
Reference20 articles.
1. Harnessing artificial intelligence (AI) to improve the well-being of all: the case for new technology diplomacy;T. Policy;Telecommunications Policy,2020
2. Computer-Human Interaction and Collaboration: Challenges and Prospects
3. Integrating context into artificial intelligence: a study from the robot collaborative technology alliance;K. E. Schaefer;Journal of Artificial Intelligence,2019
4. Unsupervised Self-Correlated Learning Smoothy Enhanced Locality Preserving Graph Convolution Embedding Clustering for Hyperspectral Images
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献