AI and Multilingualism Lab

Innovating Language, Technology and Human Communication

The SILC AI & Multilingualism Lab is an interdisciplinary research hub dedicated to advancing human-centered artificial intelligence in language education, bilingual communication, cultural studies and the humanities.

Bringing together faculty, graduate students and collaborators across ASU and international institutions, the lab integrates linguistics, artificial intelligence, computational modeling, literature, education and public health.

The lab’s mission is to develop ethical, transparent and socially responsible AI tools that enhance multilingual learning, support vulnerable communities and deepen our understanding of human communication across languages and cultures. Through collaboration with ASU’s School of Computing and Augmented Intelligence (SCAI), the School of Mathematical and Statistical Sciences, Biomedicine and global research partners, the lab positions SILC at the forefront of AI-driven multilingual research.

Students at all levels actively participate in research, gaining hands-on experience in computational linguistics, AI development, educational technology and digital humanities — preparing them for careers in global industries, education, healthcare and technology.

Our impact

The SILC AI & Multilingualism Lab:

Advances ethical, human-centered AI
Supports multilingual and low-resource communities
Bridges the humanities and computational sciences
Trains students for careers in global industries, education, healthcare, and technology
Positions SILC as a leader in the future of language education and AI

By combining multilingual expertise with cutting-edge AI research, the lab positions SILC as a national leader in the future of language, technology and global communication.

Research areas and faculty projects

AI and Human-Centered Language Education

Lead: Olga Kellert

This research explores how authentic student–teacher interaction data can be used to build reliable datasets for AI applications in language education. The goal is to design transparent, interpretable, and ethically responsible AI tools that support human-centered language learning rather than replace it.

By systematically analyzing classroom interactions, this work contributes to the development of AI-assisted tutors that enhance student engagement, communication, and learning outcomes.

This interdisciplinary initiative involves collaboration between SILC and SCAI, with graduate student researchers contributing across linguistics and artificial intelligence. Faculty collaborators include Marta Tecedor and Michael Gradoville.

Impact:

Ethical AI for language education
Transparent AI tutoring systems
Student training in AI + linguistics research

AI and Health Education in Vulnerable Bilingual Communities

Lead: Olga Kellert

This internationally funded research applies AI and computational methods to improve health communication in vulnerable bilingual communities, particularly Spanish–Quechua speakers in Ecuador and Peru.

Originally supported by the German Research Foundation (DFG), the project combines linguistics, public health, and computational analysis to examine how bilingual populations access and interpret health information.

At ASU, the project continues through advanced computational and statistical modeling in collaboration with students in mathematics, statistics, and biomedicine.

Impact:

AI for public health communication
Support for low-resource bilingual communities
Global partnerships in Peru, Ecuador and Germany

AI and Bilingual Communication

Lead: Olga Kellert

This research program uses large language models (LLMs) and computational tools to study bilingual communication, particularly in low-resource languages.

Key initiatives include:

BILINGUA Parser – Computational modeling of bilingual language structure
Multilingual Topic Modeling – AI-driven analysis of multilingual discourse
Agentive AI – Investigating cognitive and agentive dimensions of AI in bilingual processing

These projects bring together SILC, SCAI, the University of A Coruña (Spain) and international collaborators.

Impact:

AI for public health communication
Support for low-resource bilingual communities
Global partnerships in Peru, Ecuador and Germany

Hylas Project: AI and Classical Languages

Lead: Mike Tueller

The Hylas Project is an AI-driven system that algorithmically scans ancient Greek and Latin poetry without human intervention. It has achieved 100% tested accuracy across a dataset of 250,000 lines of ancient poetry.

Currently, the project is being expanded with a more robust machine learning framework, advancing digital humanities research in classical studies.

Impact:

AI applications in classical philology
Digital humanities innovation
Computational analysis of ancient texts

AI Conversation Partners

Language Buddy

Lead: Kristin Elwood, along with the German, French and Spanish programs

Developed as part of the ASU AI Innovation Challenge through the German program and initially pilot tested in their courses, SILC has coordinated with EdPlus, Enterprise Technology, and the Learning Engineering Institute to expand the Language Buddy project. This AI agent prototype is integrated in Canvas to allow online students to experience real time conversation practice based on pre-set curricular scenarios. Mariana Bahtchevanova, Teaching Professor of French, and Duncan Lien, Instructor of German, provided initial beta testing, and we are currently conducting data analysis in sections of SPA 101 taught by Steven Flanagan, Associate Teaching Professor and Director of Spanish Second Language Acquisition, and Luiza Zanchi Instructor of Spanish.

Japanese ChatGPT

Lead: Aya Nakanishi McDaniel

The Japanese program has begun to test the use of similar prompt engineering language with ASU’s OpenAI ChatGPT, building on the initial version of Language Buddy that was tested in German courses.

Student Conversation Practice

Lead: David Parks

Being developed by SILC Learning Support Services, this project aims to create an AI-powered foreign-language practice tool for students who want extra, low-stakes conversation practice outside of class. The intent is to provide interactive, scaffolded, voice-based dialogues that adjust in real time to a learner’s level and interests, helping build listening and speaking skills through natural conversational flow.

Impact:

AI conversation partners for language learners
Increased student speaking practice
Technology-enhanced curriculum innovation

Student Tutoring and Support

Lead: David Parks

Being developed by SILC Learning Support Services, this project aims to create an AI-powered tutoring tool for language learners. The intent is to help students get answers to specific language questions, help clarify what kind of support they might need, and connect them to targeted practice, learning guidance, and study strategies. The tool will also point students to relevant SILC/ASU resources and opportunities.

Impact:

AI tutoring and support for language learners
Increased student engagement
Technology-enhanced curriculum innovation

AI-Mediated L2 Interaction & Communication

Lead: Marta Tecedor

This research cluster investigates how AI-powered tutors shape second language (L2) communication, perception, and learning outcomes.

Key projects include:

AI-L2 Conversations & Willingness to Communicate

Examines how students’ attitudes toward AI influence their willingness to speak in AI-mediated vs. human interactions. Findings highlight the importance of digital literacy and learner disposition in AI-based education.

Sequence Organization in AI Conversations

Analyzes conversational structure in AI–learner exchanges using Conversation Analysis, exploring how learners treat AI as an interactional partner.

AI and L2 Speech Perception

Studies how dialect-specific AI bots influence learners’ perceptual adaptation to phonetic variation in Spanish.

Error Correction in AI Conversations

Investigates whether AI tutors can create meaningful form-focused learning episodes through corrective feedback.

Writing with AI (with Ilona Elola)

Examines how heritage and L2 learners use AI tools like ChatGPT during collaborative writing tasks, using Activity Theory to analyze decision-making and learning processes.

Impact:

Evidence-based AI integration in L2 curricula
Research on digital literacy and learner psychology
Pedagogical innovation grounded in interaction analysis

AI, Literature and Emotional Environments

Lead: Madalina Meirosu

This humanities-focused research explores how literature has historically shaped emotional responses to artificial beings and intelligent machines.

Book Project: Feeling AI: Environments of Emotion in Literature and Technology, 1815–1940

Examines how Central European literature embedded artificial beings in emotional and environmental contexts — shaping public perception of technology. Related work includes published scholarship on artificial bodies and emotion in German literature.

Courses such as:

Artificial Humans and Emotion
AI in Literature and Film
AI, Power and the Human Imagination

extend this research into the classroom. Meirosu also developed Gigi the Study Buddy, a GPT-based writing companion for students.

Impact:

Historical and cultural perspectives on AI
Humanities-driven AI ethics and imagination
Integration of AI tools into literature instruction

CulturaLens Project

Lead: Kristin Elwood and David Parks

The CulturaLens project is being developed as part of The College of Liberal Arts and Sciences AI Academy. This project explores how an interactive, AI-supported experience can help people navigate language and communication across different cultural contexts. Through guided reflection rather than one-to-one translation, it aims to support learning and understanding while informing research on intercultural communication.

Impact:

Explore cross-linguistic competence and intercultural communication
Encourage campus and community engagement
Spotlight SILC courses, programs, and career fields