Researchers compare native English speakers and Japanese second-language learners in processing globally ambiguous sentences

People often seem to understand language before they have actually heard enough words to determine its structure. In everyday conversation, listeners react immediately, anticipate what others will say, and rarely wait for a sentence to finish. This raises the question of how the brain is able to keep up with such rapid communication.

In a new study, an international team of researchers, led by Associate Professor Chie Nakamura from the School of International Liberal Studies, Waseda University, Japan, investigated how listeners interpret structurally ambiguous sentences in real time using eye-tracking technology.

The team also included Professor Suzanne Flynn from the Massachusetts Institute of Technology, United States, Professor Yoichi Miyamoto from The University of Osaka, Japan, and Professor Noriaki Yusa from Miyagi Gakuin Women’s University, Japan. Their findings have been published in the journal Frontiers in Language Sciences on March 04, 2026.


In this study, the researchers leveraged ambiguous sentences and the visual-world eye-tracking paradigm to observe how interpretation develops moment by moment during spoken comprehension. They found that listeners commit to one syntactic interpretation even while the sentence remains structurally ambiguous. Rather than passively waiting for grammatical information to unfold, listeners actively build sentence structure in real time.

“We often assume we understand a sentence only after hearing enough words to determine its structure. Our findings show that the brain actively builds sentence structure as the sentence unfolds, predicting how the sentence will continue before all the information is available,” highlights Nakamura.

Using eye-tracking during spoken comprehension, the researchers found that listeners commit to one syntactic interpretation even when the sentence remains structurally ambiguous. The results reveal that listeners adopt a preferred syntactic structure prior to receiving explicit structural confirmation. By comparing English and Japanese and examining native English speakers and Japanese speakers learning English as a second language, the researchers found that predictive processing depends on language structure. English speakers rapidly favor one interpretation, whereas Japanese speakers show a different timing and pattern. Japanese L1 speakers who are L2 learners of English also adjust their predictive strategy to English rather than simply transferring their native-language processing. These results indicate that comprehension is proactive structure building, not passive decoding, and provide new insight into how the brain processes language and how bilinguals understand a second language.

The findings help explain why listening in a second language can feel difficult even when the words are known. Comprehension depends on predicting sentence structure in real time, and this prediction is tuned to each language. Learners therefore cannot rely only on vocabulary or translation; they must also learn how the language organizes sentences. According to Nakamura, “This has implications for language teaching, suggesting that language learning involves more than acquiring vocabulary. Exposure to natural sentence patterns and listening practice may help learners develop the real-time processing skills needed for successful comprehension.”

Beyond language learning, the results are relevant to communication in noisy or fast-paced environments, such as classrooms, conversations, or online meetings. Because listeners rely on structural predictions, comprehension can break down when speech unfolds unexpectedly or too quickly.

The findings may also inform the development of speech recognition systems and language-learning technologies by encouraging models that anticipate likely sentence structures rather than processing words only after they occur.

Reference
Authors: Chie Nakamura¹, Suzanne Flynn², Yoichi Miyamoto³, and Noriaki Yusa⁴
Title of original paper: Lexical vs. Structural Cue Use in L2 Prediction: Filler-Gap Parsing Ability Shapes Learners’ Information Use
Journal: Frontiers in Language Sciences
DOI: https://doi.org/10.3389/flang.2026.1756463
Affiliations:
¹School of International Liberal Studies, Waseda University
²Department of Linguistics and Philosophy, Massachusetts Institute of Technology
³Graduate School of Humanities, The University of Osaka
⁴Department of English Faculty of Liberal Arts, Miyagi Gakuin Women’s University

About Waseda University
Located in the heart of Tokyo, Waseda University is a leading private research university that has long been dedicated to academic excellence, innovative research, and civic engagement at both the local and global levels since 1882. The University has produced many changemakers in its history, including eight prime ministers and many leaders in business, science and technology, literature, sports, and film. Waseda has strong collaborations with overseas research institutions and is committed to advancing cutting-edge research and developing leaders who can contribute to the resolution of complex, global social issues. The University has set a target of achieving a zero-carbon campus by 2032, in line with the Sustainable Development Goals (SDGs) adopted by the United Nations in 2015.
To learn more about Waseda University, visit https://www.waseda.jp/top/en

About Associate Professor Chie Nakamura
Chie Nakamura is an Associate Professor in the School of International Liberal Studies (SILS) and the Graduate School of International Culture and Communication Studies (GSICCS), both at Waseda University, Japan. She received her PhD from the Graduate School of Science and Technology, Keio University, Japan, in 2013 and subsequently conducted postdoctoral research at the University of Tokyo, Massachusetts Institute of Technology (MIT), and University of California, Los Angeles (UCLA). Her research focuses on psycholinguistics, sentence processing, and second-language acquisition, using experimental methods such as eye-tracking and other neurolinguistic approaches to investigate how the brain processes language in real time. Her work also aims to develop theoretical and computational models of bilingual language comprehension. She has authored numerous widely cited papers in these fields. She was chosen for the Waseda Research Acceleration Program for Early-Stage Principle Investigators in 2025 and received the Waseda University Teaching Award for AY 2024.