Output Analysis in Voice Interaction in AI Environment

The future foreign language teaching will inevitably be combined with AI technology, and it is likely that the traditional foreign language teaching method of one teacher instructing a number of students will gradually be completely replaced by a new foreign language learning mode of each student’s foreign language learning and most importantly acquisition being realized by interacting with AI interface customized for each student. The reason is rather simple. In spite of numerous repatching teaching method explorations, the traditional classroom-based foreign language teaching has been unable to solve the congenital problems, such as inadequacy of language input and interaction, insufficiency of real life sensory stimulation and violation of natural language acquisition sequence for the absence of language environment. The AI interface, in contrast, with the infinite, accurate and real language supply and human-computer interaction, and also with constant adjustment of ZPD (Zone of Proximal Development) according to each student's language development level, precisely sets up appropriate scaffolding for every language learner, thus revolutionarily creating a language environment close to or even beyond the real one and returning language learning to natural acquisition process. The first step to achieve this goal is to realize human-computer voice interaction. The realization of voice interaction needs many technical supports, among which voice interaction output analysis is an urgent part. By importing AI voice interactive output analysis algorithm, constructing output analysis model, and establishing the operation platform of the analysis model, the paper relies on the determination of the voice interactive output influence function, and takes the cultural elements of English language as an example to analyze the output.