AI takes center stage at world Chinese language conference

A global push to digitize Chinese learning

Beijing opened the 2025 World Chinese Language Conference with a clear message that artificial intelligence is moving from pilot projects to practical tools in classrooms around the world. Under the theme “Innovation Leads, AI Empowers: Learning Chinese Without Borders,” the gathering drew nearly 5,000 participants from more than 160 countries and regions. Organizers presented new platforms that aim to make Chinese learning more adaptive, more accessible, and more connected to real teaching needs.

Chinese Vice Premier Ding Xuexiang said the country would keep supporting international Chinese language education and expand partnerships that link language study with real world skills. He called for smart campuses, smarter classrooms, and deeper sharing of digital resources, with the goal of making learning Chinese more convenient and efficient. That policy push comes as interest in Chinese continues to grow, driven by trade, study, and cultural exchange.

Inside the new AI toolkit announced in Beijing

The conference unveiled a group of technologies designed to serve both teachers and learners. The rollout included a knowledge graph for international Chinese education standards, a large language education corpus, a new adaptive assessment product called HSK GO, an AI cloud that creates lesson materials in seconds, and a smart classroom setup led by a virtual teacher named Xiao Yu.

Knowledge graph and education corpus

The new knowledge graph integrates 380,000 language nodes and about one million semantic relationships. In simple terms, a knowledge graph maps how concepts connect. For Chinese, that can mean linking characters, words, grammar points, topics, and cultural references so that software can see relationships across texts and curriculum standards. When a learner struggles with a grammar pattern or a tone pairing, the system can find related examples and targeted exercises based on those relationships.

The companion corpus aggregates large volumes of language data to support multimodal queries and deep analysis. Multimodal means learners and teachers can search and study across text, audio, and sometimes images or video. A teacher preparing a unit on food, for example, can retrieve graded dialogues with correct tone patterns, find sample menus with characters and pinyin, and pull authentic clips that match students’ proficiency levels.

Adaptive assessment with HSK GO

HSK GO uses AI to tailor assessment paths to each learner. HSK is the standard proficiency test for Chinese (Hanyu Shuiping Kaoshi). Adaptive assessment adjusts question difficulty in real time as a student answers, which helps reveal a more accurate picture of current ability. By connecting to curriculum standards and past performance, the system can propose the next set of tasks, suggest review targets, and estimate progress toward specific HSK bands.

AI cloud and the smart classroom with Xiao Yu

An AI cloud platform trained with data from 3,000 Confucius Institutes can generate lesson plans and slide decks after a teacher selects textbook parameters. The goal is to reduce routine preparation time and free teachers to focus on feedback, conversation practice, and culture. In the smart classroom model, a virtual teacher named Xiao Yu supports voice synthesis, speech evaluation, and intelligent assessment. This setup is designed for schools that lack qualified Chinese teachers, offering a way to deliver consistent instruction and practice while local staff handle supervision and community engagement.

Why these tools matter for learners and teachers

Many schools want to add Chinese, yet struggle to hire trained teachers, build curricula, and provide sustained practice in speaking and listening. AI driven tools can close some of those gaps. Adaptive systems individualize pacing, pronunciation assessment provides immediate guidance on tones and finals, and auto generated materials reduce preparation time. For students, regular feedback builds confidence. For teachers, analytics reveal where a class is progressing or getting stuck, which supports targeted instruction.

These systems are not a replacement for human teachers. Culture, humor, pragmatics, and real communication still depend on human interaction. The opportunity lies in combining AI for precision coaching and content delivery with teacher expertise in context, motivation, and community building.

Evidence from classrooms and labs

Real world trials and research give a clearer picture of what works. Chinese Testing International, the organization behind HSK, has built pronunciation training on Azure AI Speech. Its Learn Pronunciation to HSK application gives instant feedback on individual sounds, tone contours, and whole sentence rhythm, then loops students through practice until they reach a set threshold. The content spans words, phrases, dialogues, tongue twisters, and classic poems, so learners experience both daily language and literary style. CTI has set up more than a thousand test centers in over 160 countries and reports that AI speech scoring has improved consistency, saved time, and supported a full cycle of teaching, practice, testing, and assessment.

In Southeast Asia, a study of learners at Confucius Institutes examined what keeps students using AI chatbots for Mandarin practice. The research combined technology acceptance and motivation frameworks and identified several drivers of sustained use. Performance expectancy, the belief that the chatbot actually improves learning, matters. Effort expectancy, how easy the system is to use, also matters. Facilitating conditions, such as network quality and technical support, create a foundation for steady engagement. Social influence from teachers and peers boosts motivation and satisfaction, which then support continued use. The practical takeaway is straightforward: align chatbot tasks with course goals, simplify interfaces, provide support, and create adaptive prompts that match level and interest.

There is also growing evidence about how AI feedback affects the emotional side of language learning. Research with university students learning English in China found that corrective and motivational AI feedback encouraged self reflection and supported creativity in writing and speaking. Familiarity with AI tools and the style of feedback delivery affected anxiety, and well designed feedback increased learners’ resilience when they hit obstacles. These findings translate well to Chinese instruction, where tone accuracy, character learning, and pragmatic choices can feel intimidating without timely guidance.

The human teacher in an AI classroom

Educators who work with AI in language instruction tend to land on the same point. AI can deliver adaptive practice at scale, but the relationship between teacher and learner remains the heart of the class. Cultural nuance, situational language choices, and values are best explored with a human guide. Experienced teachers also shape the emotional climate of a class, which has a direct effect on persistence and progress.

Teacher preparation is a critical factor. Recent work on an AI readiness scale for teachers of Chinese as a foreign language points to three areas. Personal assets include technological knowledge for teaching and a willingness to try new tools. Value and cost beliefs cover perceived benefits and concerns, such as time investment. Contextual resources include institutional support and enabling conditions. These factors together influence satisfaction with AI and the intention to keep using it. Programs that invest in training, peer support, and practical guides are more likely to see sustained gains.

Apps, avatars, and agents for self study

A growing set of consumer apps gives learners ways to practice beyond the classroom. Conversation focused platforms let users speak with AI that adapts to level and topic, then returns immediate feedback. Some services now use voice models built from native speakers to increase the feeling of a real conversation. Reviewers point out strengths like flexible role plays, feedback reports, and vocabulary integration across practice modes. They also note common issues, such as occasional mishearing of tones, voices that feel robotic, and limited gamification that requires self motivation to keep a study streak.

Tutor style apps build on structured curricula and short sessions. One popular service offers eight levels across 170 topics with hundreds of ten minute lessons. Its embedded AI, presented as a personal tutor, explains errors, suggests better phrasing, and gives real time feedback on grammar and word choice. Tools cover pinyin, character structure, essential HSK vocabulary, and everyday expressions. These apps are designed by native speaking teachers, with AI used to scale coaching and adapt to learner answers.

Newer platforms blend language learning with cultural immersion. Talkmate’s International Chinese Education AI Agent presents AI avatars of more than 100 cultural figures and supports conversations in six major languages, with plans to expand. Learners can discuss poetry, history, and philosophy at advanced levels, or start with cross cultural modules that compare familiar topics to Chinese contexts. The model aims to keep practice personal and engaging while preparing learners for HSK exams with over 5,000 guided lessons.

A company statement about a related product launch captured the ambition behind these systems.

HanLink marks a transformative leap in language education. By integrating AI with cultural exchange, we are proud to support Saudi Arabia’s local students.

In Saudi Arabia, a four week pilot of HanLink with 500 students reported an 80 percent homework accuracy rate, an average oral score of 75 out of 100, and steady self guided practice of 15 minutes per day. Features include real time pronunciation correction, character writing analysis, more than 180 conversation scenarios, and continuous AI tutoring. Teacher tools offer automated grading and dashboards to track progress from the class to the individual. The company plans to expand the program after the pilot.

Policy, partnerships, and cultural exchange

Speakers at the conference tied AI progress to real cooperation across borders. Ding Xuexiang encouraged programs that link international Chinese education to vocational and professional training, so learners can use Chinese in workplace contexts. He called for more partnerships between Chinese and foreign schools, more student exchanges, and wider access to competitions like Chinese Bridge. Government, universities, and organizations were urged to share digital resources and build smart classrooms that connect learners at different sites.

International guests highlighted that language learning is also about people. Leaders from Chile, Thailand, Egypt, and Uzbekistan spoke about Chinese as a bridge that supports relationships in trade, culture, and education. They welcomed AI as a support for access and equity, while affirming that person to person dialogue holds value that machine translation cannot replace.

Risks and constraints to watch

Even the best tools have limits. Speech recognition can misjudge tones when the audio is noisy or the accent is unfamiliar. AI voices sometimes sound flat, which reduces the feeling of a real exchange. Without careful design, systems may push learners into content that is too easy or too hard. Data privacy and security require clear policies and transparent handling of student recordings and performance data. Schools should understand which data are stored, where they are processed, and who has access.

Access is another challenge. Reliable internet, microphones, and quiet spaces are not guaranteed in every program. Without teacher training and technical support, new tools can sit unused or create extra work. Budget planning should account for subscriptions, equipment, and training hours, not just the launch announcement.

The job market is also shifting. Translation tasks that once required junior staff are increasingly handled by AI with high accuracy at low cost. Chinese universities have already scaled back some foreign language majors, and graduates report fewer direct language jobs in trade, translation, and basic tutoring. That change does not erase the need for human experts. It raises demand for language skills combined with law, business, data, or area studies. Programs that help students build these combinations will be better aligned with future roles that require creativity, judgment, and collaboration with technology.

How schools and programs can get started responsibly

Successful AI adoption starts with clear goals. Decide what problem you want to solve. For example, a program might target tone accuracy for beginners, consistent speaking assessment across sections, or faster preparation of graded reading materials. Select tools that map to those needs and to your curriculum, such as HSK aligned practice or content that matches your own syllabus.

Practical steps backed by research

Run a pilot with a small group before a wider rollout, then review data on performance, engagement, and satisfaction. Keep interfaces simple so students can start quickly. Provide teacher workshops that cover both technical setup and classroom use. Align chatbot or conversation tasks to lesson objectives so practice feels purposeful. Build in emotional support, including clear explanations and encouraging feedback styles, since that reduces anxiety and builds resilience. Document data practices and secure consent, especially for voice recordings. Share success stories and pain points across departments so teams can improve the model and support new adopters.

What to Know

• China introduced a suite of AI tools at the World Chinese Language Conference, including a standards based knowledge graph, a large education corpus, HSK GO, an AI cloud for lesson materials, and a smart classroom with a virtual teacher
• Vice Premier Ding Xuexiang urged smart campuses, resource sharing, and integration of international Chinese education with vocational and professional training
• CTI’s AI pronunciation training on Azure AI Speech supports fast feedback across many difficulty levels and helps scale consistent assessment worldwide
• Research on chatbot use in Confucius Institutes highlights performance expectancy, ease of use, support conditions, and social influence as drivers of continued engagement
• Studies show AI feedback can strengthen self reflection, creativity, and resilience, especially when learners are familiar with the tools
• Teachers remain central for cultural nuance and motivation, and teacher readiness depends on personal assets, value and cost beliefs, and institutional support
• Consumer apps offer conversation practice and structured tutoring, while platforms like Talkmate and HanLink blend language learning with cultural exploration
• Limits include tone recognition errors, robotic voices, uneven leveling, and concerns about data privacy and security
• AI is changing entry level translation work, which raises demand for language skills combined with law, business, data, or other fields
• Practical adoption steps include targeted pilots, training, simple interfaces, clear data policies, and alignment with course objectives