1 Introduction

The teaching of English for Specific Purposes (ESP) faces both opportunities and challenges of technological integration, and the era of artificial intelligence has driven the development of computer-assisted language learning (CALL). The Ministry of Education's "Education Informatization 2.0 Action Plan" emphasizes the use of technologies such as artificial intelligence and big data to transform education models. Artificial intelligence technology has achieved significant results in foreign language education, capable of intelligently screening learning materials, automatic grading, providing feedback, creating virtual language environments, and promoting learners' language abilities and deep learning. Artificial intelligence technology also helps ESP teachers provide professional and personalized guidance, discover patterns and relationships in big data, transform teaching models, and improve teaching quality. This article is based on the construction and application of financial English corpus, exploring the path of ESP corpus construction assisted by artificial intelligence, and providing inspiration for ESP teaching in universities.

New progress in ESP teaching and curriculum corpus research

The ESP course aims to cultivate students' English communication skills in specific subjects, and its teaching research has gone through three stages: based on learning skills, based on subject texts, and based on literacy practice. As the role of learners in language learning is increasingly valued, ESP teaching is gradually shifting towards social practice, focusing on communicative genres, rhetoric, and literacy skills in the target language. The integration of corpus and ESP course teaching is becoming increasingly close, but China lags behind foreign countries in the construction of English subject corpora. Corpus based ESP research mainly focuses on linguistic feature description, lacking the application of artificial intelligence corpus building software and data analysis software. This article takes the construction and application of financial English corpus as an example to explore how artificial intelligence can assist in the construction and application of ESP, providing new ideas for ESP teaching models in China.

3 Foundations of Artificial Intelligence Assisted ESP Corpus Construction

Artificial intelligence assisted ESP corpus is widely used in teaching, and its construction mechanism is of great significance for integrating financial subject teaching knowledge and enhancing practical teaching of financial corpus courses. The development of artificial intelligence technology is based on information theory and has a natural connection with linguistics, requiring basic language processing methods and logical operations. The construction of ESP corpus involves various artificial intelligence technologies and natural language processing tools, such as web crawling tools, NLTK, Stanford CoreNLP, etc., to help researchers efficiently and standardly complete corpus collection, processing, and visualization. The construction of an artificial intelligence assisted ESP corpus combining information theory and linguistic theory can fully respect the rules of English language, reflect the characteristics of language application, and visually display language phenomena at different levels. The ESP corpus developed based on artificial intelligence allows students to learn professional knowledge while also being exposed to authentic English language elements, promoting efficient absorption of language knowledge and enhancing language skills.

4. Design of AI assisted Financial English Corpus

Discussed the design of an AI assisted financial English corpus, including the definition, selection, and processing of the corpus. The construction of the Financial English Corpus is based on the definition of finance in the New Palgrave Dictionary of Economics, covering aspects such as capital market operations, asset supply, and pricing. The corpus design follows the Sinclair principle, combined with the practice of Smith and Guangdong University of Finance, and is divided into two steps: constructing a corpus based on domain theory and integrating it into the ESP curriculum to build a teaching system. After determining the source of the corpus, artificial intelligence technology is used to collect texts of various language domains, including online resources and textbooks, extract keywords to create a mini subject terminology corpus, and compare and screen high-frequency practical word combinations with a general corpus. After collecting the corpus, preprocessing work such as data cleaning, word segmentation, and removal of stop words is carried out, and the corpus is annotated with parts of speech, semantics, syntax, etc. to enhance research value and application scope. Artificial intelligence assisted ESP corpus improves the efficiency of corpus acquisition, processing, and analysis, while incorporating the latest technological achievements to help students master the application of artificial intelligence technology in language processing. Teachers can use corpus resources to provide financial dynamic information, enhance students' professional competence, and test teaching effectiveness through practice questions and self-study tests, adjust the difficulty of corpus materials, and improve teaching plans. Students can also use corpus analysis software and NLP tools for language translation or semantic and grammatical analysis learning, enhancing their professional competence in the subject.

5 Practical Cases of Artificial Intelligence Assisted Financial English Construction

Introduced a practical case of the construction of an artificial intelligence assisted financial English corpus. Taking the course "Financial English" as an example, students are required to use artificial intelligence tools to download financial institution news and convert it into a txt format file, forming an English corpus of financial institution news. The specific steps include: 1 Use Sketch Engine to create a mini corpus of courses and filter high-frequency practical keywords; 2. Students are grouped to use the Octopus customized process to download financial institution news corpus; 3. Process the collected corpus, including data cleaning such as alignment, deletion, and annotation; 4. Use tools such as NLTK and Standford CoreNLP for automatic word segmentation and part of speech tagging; 5. Build a financial news corpus website that supports indexing, co-occurrence, and word frequency statistics functions. Through these steps, a high-quality financial English corpus can be constructed to provide support for teaching and research.

6 Conclusion

The importance of using artificial intelligence to assist in the construction of financial English corpora has been emphasized, aiming to achieve a combination of personalized foreign language learning and professional training through the integration of educational information technology and classroom revolution. Through innovative perspectives, integrating corpus resources based on artificial intelligence assistance into ESP courses to cultivate students' interdisciplinary abilities. By combining information carriers, theoretical deduction, and in class and out of class activities, reconstruct information correlation and presentation forms to meet learning needs and stimulate teaching enthusiasm. The construction of this corpus provides intelligent support for subject English teaching and research, has enlightening effects on the teaching of similar courses, and promotes the healthy operation of the ESP curriculum system.