# An Assistant System for Translation Flipped Classroom
## 1 Introduction  
Translation courses are common in but not limited to language education. They are set in various fields that require cross-language communication, such as Business Economics, Law, and Medicine. The discipline of translation itself is also an independent degree course. The general purpose of translation is to achieve barrier-free communication or share important achievements. The rapid progress of international exchanges has brought a tremendous amount of translation needs [1; 2; 3; 4]. It is necessary to improve teaching methods to cultivate more professional solid translation talents that can meet the higher demands of modern society [5; 6; 7]. In higher education, teacher-centered methodologies suffer from a lack of opportunities for students to practice more elevated levels of thinking and a lack of connection to actual professional tasks [8]. In contrast, student-centered methodologies, such as the flipped classroom (FC), combine theoretical and practical contents and apply them to real-world problems so as to improve students' study interest and initiative [9]. FC requires students to learn the content assigned by the teacher and complete specific tasks outside the classroom. At scheduled class times, students share their work, discuss it with each other, and receive immediate feedback from the instructor [10]. This new teaching mode and the support of modern information technology develop translation teaching to focus on personalized and active learning [11]. Students have different levels of learning ability and professional proficiency. To meet the learning needs of all students, teachers have to meticulously design the content for students' pre-class learning, which will take considerable time. In addition, the effectiveness of FC depends heavily on the efficient use of classroom time [12]. Teachers need to be aware of students' learning situation beforeclass so as to reasonably arrange the time and content for presentation, discussion and guidance in class. All these works make the preparation time of FC perhaps three times that of traditional classes [13], which has led to teachers' reluctance to conduct FC. It is difficult for most teachers to devote so much time, especially when the course schedule is tight. The resulting lack of global control affects the efficiency of classroom utilization and makes it difficult for FC to play its advantages. Machine translation (MT) is a subfield of computational linguistics that can realize low-cost communication between the world's different languages through algorithms. It has the advantages of convenience, fast speed, and so on. Early MT models were based on artificial knowledge. Firstly, an accurate and universal set of rules is summarized from the monolingual, bilingual or multilingual dictionaries and grammars by linguists. The whole translation system analyzes the form, syntax, and semantics of the source language in the specific translation task, then deduces the target language with the corresponding rules. Statistical machine translation (SMT) abandons these prior linguistic rules. It learns statistical rules from massively parallel corpora and turns translation problems into probabilistic computation problems. With the fast growth of artificial intelligence, neural machine translation (NMT) has become a mainstream of research for MT. NMT, based on deep learning, adopts an end-to-end approach. The whole NMT model is represented as a large neural network consisting of millions of trained parameters, taking as input a sequence of source tokens and returning a sequence of target tokens. Although NMT is considered a revolution in MT, it cannot yet be trusted to apply independently in practical applications. It will generally require post-translation human editing, especially when the sentences to be translated are long and complex. On the one hand, MT is difficult to take full of context into account. The most basic context is the linguistic context, which needs to consider the context before and after the source text.