The language science initiative is an interdisciplinary framework among RIT faculty which comprises scholarly collaborations, student research opportunities, curricular offerings, events, networking opportunities, and community outreach. Faculty in our community are award-winning and well-funded researchers and experienced educators. Students and faculty engage in research across areas such as computational linguistics/natural language and speech processing, American Sign Language, phonetics, syntax, psycholinguistics and the psychology of language, applying computational, lab-based/experimental and fieldwork methods. We invite inquisitive undergraduate and graduate students to seek out our curricular offerings and research opportunities, useful for a range of career prospects.

Cecilia Ovesdotter Alm, Ph.D.
Associate Professor, College of Liberal Arts
Chair, Language Science Curriculum Committee
Director, Computational Linguistics and Speech Processing Lab
 +1 (585) 475-7327
Multimodal Sensing; Natural Language Understanding; Human-Centered Artificial Intelligence
Gerald P. Berent, Ph.D.
Professor Emeritus, National Technical Institute for the Deaf
Director, REACH Laboratory for Academic & Career English Studies
Associate Director, REACH Center for Studies on Career Success
 +1 (585) 475-6521
Deaf Studies; English Teaching & Learning; Second Language Acquisition; Theoretical & Applied Linguistics
Zhong Chen, Ph.D.
Assistant Professor, College of Liberal Arts
Coordinator, Chinese Program
Member, LCC
 +1 (585) 475-6917
Computational Linguistics; East Asian Languages; Experimental Syntax; Psycholinguistics
Matt Dye, Ph.D.
Assistant Professor, National Technical Institute for the Deaf
Member, NTID Center on Cognition and Learning
Affiliate Faculty, Department of Psychology
Cochlear Implants; Deaf; Sign Language; Visual Processing
Matt Huenerfauth, Ph.D.
Professor, Golisano College of Computing & Information Sciences

Director, Linguistic and Assistive Technologies Laboratory

Liason, Linguistic Data Consortium
 +1 (585) 475-2459
American Sign Language; Automatic Speech Recognition; Human-Computer Interaction
Corrine Occhino, Ph.D.
Research Assistant Professor, National Technical Institute for the Deaf
Adjunct Faculty, Department of Sociology and Anthropology — Instructor of Linguistics
Member, NTID Center on Cognition and Learning
Construction Grammar; Linguistic Variation; Signed Languages; Usage-based Phonology
Karl Reza Sarvestani
Visiting Assistant Professor, College of Liberal Arts
Instructor, Language Science Coursework
Ph.D. Candidate, Linguistics at University of Buffalo
Language Documentation; Phonetics; Phonology; Southeast Asian Languages
Tina M. Sutton, Ph.D.
Assistant Professor, Department of Psychology
Graduate Director, Experimental Psychology Program
Instructor, Language and Thought
 +1 (585) 475-6773
Bilingualism; Emotion; Language Attention
Stanley Van Horn, Ph.D.
Director, English Language Center
Instructor, Linguistic Anthropology: Language and Culture
 +1 (585) 475-6939
Applied Linguistics for Language Learning and Teaching; Cross-Cultural Communication; Discourse Analysis
CAIR is a research center in the Golisano College of Computing and Information Sciences at RIT, bringing together faculty and students who conduct and publish research at leading computing and education venues, on accessibility and assistive technology for diverse users, including people who are Deaf or Hard of Hearing (DHH), people who are blind, people with communication impairments, and older adults. Contact: Matt Huenerfauth.
The CLaSP lab at RIT is dedicated to advancing applied and theoretical research involving text, speech, and multimodal data. An area of focus is linguistic and language-inclusive multimodal sensing. CLaSP provides research opportunities for undergraduate and graduate students, and hosts a regular student research discussant series. The lab collaborates closely with other research groups on campus. Contact: Cecilia Ovesdotter Alm.
The LATLab conducts research in computational linguistics and human-computer interaction, with a primary focus on accessibility applications and assistive technology for people with disabilities. The lab focuses specifically on technologies for people who are deaf and hard-of-hearing (DHH) or individuals with low English literacy. Contact: Matt Huenerfauth.
This research project undertakes a comprehensive investigation of deaf college students' knowledge of isolatable lexical properties of verbs using sentence acceptability rating scale tasks. Deaf learners' English verb knowledge within and across the relevant lexical domains is compared to the verb knowledge of their hearing college-level peers and hearing second-language (L2) learners of English, whose English acquisition exhibits many parallels with deaf learners' acquisition. Contact: Gerald P. Berent.
This project is investigating techniques for making use of motion-capture data collected from native ASL signers to produce linguistically accurate animations of American Sign Language. In particular, this project is focused on the use of space for pronominal reference and verb inflection/agreement. This project also supported a summer research internship program for ASL-signing high school students, and REU supplements from the NSF have supported research experiences for visiting undergraduate students. Contact: Matt Huenerfauth.
Linguine is an educational tool that integrates computational linguistics resources for use in non-technical undergraduate language science courses. By using the tool in conjunction with evidence-driven pedagogical case studies, we strive to provide opportunities for students to gain an understanding of linguistic concepts and analysis through the lens of realistic problems in feasible ways. Linguine has potential to encourage students across training backgrounds to continue on to computational language analysis coursework. Contact: Cecilia Ovesdotter Alm.
Sensing Surprise using Speech and other Modalities
This interdisciplinary team project involves collecting a corpus, analyzing, and making computational inference about intuitive surprise. We focus on multimodal, language-inclusive expression (spoken language, facial expression, biophysical responses), elicited during two interactive game tasks. The objective is to gain insight into how to characterize surprise for developing more realistic, human-centered AI systems capable of affective understanding or expression for improved human-machine interaction and collaboration. Contact: Cecilia Ovesdotter Alm.
Language Science
The Language Science Minor provides students with the knowledge of how sounds, structure, and meaning work in human language, and the skills needed to apply that knowledge in disciplines such as computing, psychology, interpreting, and engineering. Students are encouraged to pursue their individual career interests in language, from the relationship between language and culture to the cognitive underpinnings of language to the tools and methods powering language technology in artificial intelligence. Housed in College of Liberal Arts.
Language Science
The Language Science Immersion prepares students in the interdisciplinary scientific study and analysis of human language. Language science is directly applicable to students interested in computing and media, human-computer interaction, brain and cognition, language acquisition, human health, interpreting, relevant branches of engineering, and policy studies. Students can complete the immersion irrespective of their skills in languages other than English. In addition to a core course on linguistic principles, students can choose electives covering technology of language, philosophy of language, and language in culture and society. Housed in College of Liberal Arts.
Computational Linguistics & Human Language Technology
The Computational Linguistics & Human Language Technology Immersion provides exposure to computational linguistics and relevant language science course work. Students gain knowledge and practical skills in computational natural language processing and technical linguistic analysis, useful for analytics and modeling with language data and for developing, evaluating, and maintaining language technology software. Housed in Department of English in College of Liberal Arts.
Application Domain
Computational Linguistics (in Software Engineering)
Many software applications involve processing natural language text or speech data. This application domain provides exposure to computational linguistics and language science. Students gain knowledge and practical skills in computational natural language processing and technical linguistic analysis, useful for analytics and modeling with language data and for developing, evaluating, and maintaining language technology software. Students can earn a minor in language science with two additional electives.
Graduate Course
ENGL 681: Introduction to Natural Language Processing
This graduate course provides theoretical foundation as well as hands-on (lab-style) practice in computational approaches for processing natural language text. The course will have relevance to various disciplines in the humanities, sciences, computational, and technical fields. We will discuss problems that involve different components of the language system (such as meaning in context and linguistic structures). Students will additionally work on modeling and implementing natural language processing and digital text solutions. Students will program in Python and use a variety of relevant tools. Prerequisite(s): Programming skills, demonstrated via coursework or instructor approval.
Graduate Course
ENGL 682: Seminar in Computational Linguistics
This graduate course gives students an opportunity to study a focus area of increased complexity in computational linguistics. The focus varies each semester. Students will develop skills in computational linguistics analysis in a laboratory setting, according to professional standards. A research project plays a central role in the course. Students will engage with relevant research literature, research design and methodology, project development, and reporting in various formats. Prerequisite(s): Completion of ENGL 681 or instructor approval.
Graduate Course
ENGL 684: Spoken Language Processing
This graduate course introduces students to speech and spoken language processing with a focus on real-world applications including automatic speech recognition, speech synthesis, and spoken dialog systems, as well as tasks such as emotion detection and speaker identification. Students will learn the fundamentals of signal processing for speech and explore the theoretical foundations of how human speech can be processed by computers. Students will then collect data and use existing toolkits to build their own speech recognition or speech synthesis system. This course provides theoretical foundation as well as hands-on laboratory practice.
Language Science & Computational Linguistics Student Excellence Award
Awarded annually to undergraduate and graduate students for demonstrated excellence in language science/computational linguistics, with attention to project/research achievements. Nominations are made by the Language Science Faculty and juried by the Language Science Curriculum Committee (LCC) in Spring. Students currently enrolled in undergraduate or graduate programs at RIT are eligible for nomination. The award includes a certificate of achievement and a monetary gift.
Distinguished Computational Linguistics Lecture
Previous visiting distinguished speakers include:
Minor and Immersion Fair Exhibit
Language Science is respresented at the annual College of Liberal Arts Minor and Immersion Fair.
Language Science Faculty Research Mixers
Language science faculty and postdoctoral scientists connect to present and discuss scholarly work.

2018 Imagine RIT exhibit. Top: Jordan Shea (left) and Benjamin Meyers (right) describing their work in the CLaSP lab. Bottom: Jordan Shea (left), Cissi O. Alm (center), and Benjamin Meyers (right).

Faculty Research Mixer, Spring 2018. Left to right: Joseph Bochner (NTID), Matt Huenerfauth (GCCIS), Stan van Horn (English Language Center), Karl Sarvestani (CLA), Jerry Berent (NTID), Hiroko Yamashita (CLA), Zhong Chen (CLA), Cissi Ovesdotter Alm (CLA), and Susan Rizzo (NTID).
For information about language science and computational linguistics at RIT, please contact the Linguistics/Language Science Curriculum Committee (LCC) Chair, Cecilia Ovesdotter Alm.
 +1 (585) 475-7327
For information regarding specific research groups and projects, please consult the appropriate linked website(s) for contact information.
Other Members of the Language Science Curriculum Committee (LCC):
  • Gerald P. Berent
  • Zhong Chen
  • Matt Huenerfauth