Affiliation
Ph.D. Student, Carnegie Mellon University, United States
Education
2024-Present: Ph.D. in Applied Linguistics & SLA, Carnegie Mellon University, United States
2022-2024: M.A. in Engineering, Waseda University, Japan
2018-2019: Student Exchange Program, St. Petersburg State University, Russia
2017-2022: B.A. in Liberal Arts, Waseda University, Japan
Research
My research interests lie in the effective assessment, feedback, and learning assistance of L2 speech utilizing AI techniques. More specifically, I have conducted research of automated scoring systems for L2 oral fluency. During my master’s program, I involved in a research project on AI conversational agent for L2 English testing and examined the impacts of an AI-driven diagnostic assessment for L2 spoken vocabulary. Extending this line of research, my Ph.D. study aims to develop and validate spoken dialogue systems that assist the learning of L2 productive knowledge and skills.
In addition, I am interested in advancing research methodologies in SLA using state-of-the-art AI technologies. I developed a system to automatically annotate the full range of oral fluency features (i.e., syllables, disfluency words and pause locations). I am open to collaborating with researchers worldwide by automatizing L2 data annotations and analyses.
Recent Publication
Suzuki, S., Takatsu, H., Matsuura, R., Koyama, M., Saeki, M., & Matsuyama, Y. (in press). Feedforwarding Diagnostic Language Assessment: AI-Driven Weakness Identification and Contextualised Feedback for L2 Speaking. Language Testing.
Matsuura, R., Suzuki, S., Takizawa, K., Saeki, M., & Matsuyama, Y. (2025). Gauging the Validity of Machine Learning-Based Temporal Feature Annotation to Measure Fluency in Speech Automatically. Research Methods in Applied Linguistics, 4(1), 1-23. https://doi.org/10.1016/j.rmal.2024.100177
Saeki, M., Takatsu, H., Kurata, F., Suzuki, S., Eguchi, M., Matsuura, R., Takizawa, K., Yoshikawa, S., & Matsuyama, Y. (2024). InteLLA: Intelligent Language Learning Assistant for Assessing Language Proficiency Through Interviews and Roleplays. Proc. of SIGDIAL 2024, 385-399. https://aclanthology.org/2024.sigdial-1.34/
Matsuura, R. & Suzuki, S. (2023). Prompt-independent Automated Scoring of L2 Oral Fluency by Capturing Prompt Effects. Proc. of Artificial Intelligence in Education (AIED). doi: https://doi.org/10.1007/978-3-031-36272-9_62
Matsuura, R., Suzuki, S., Saeki, M., Ogawa, T., & Matsuyama, Y. (2022). Refinement of Utterance Fluency Feature Extraction and Automated Scoring of L2 Oral Fluency with Dialogic Features. Proc. of Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). 1312-1320. doi: https://doi.org/10.23919/APSIPAASC55919.2022.9980148
Scholarship
April 2022 – March 2024: JPC Scholarship Foundation (JPC奨学財団).
- Amount awarded: JPY 720,000 (approx. USD 5,100).
April 2024 – March 2027: Japan Society for the Promotion of Science Doctoral Course (DC) Research Fellowship.
Amount awarded: JPY 7,200,000 (approx. USD 51,000).
I declined the fellowship because I started a Ph.D. program outside Japan.
August 2024 – May 2028 (expected): Dick Tucker SLA Fellowship.
- Amount awarded: (USD 2,500 per month).
Patents
Dynamic Speaking Assessment (Japan 2024-114919; 2024年7月18日)
Speaking Proficiency Assessment (Japan 2023-177296; 2023年10月14日)
Contact
- Email: rmatsuur[at]andrew.cmu.edu