Sarina is a linguist with expertise in bilingualism, low-resource languages, syntax, and computational linguistics. I have hands-on experience working with North American Indigenous languages, including digitizing dictionaries, language documentation, corpus development, and data annotation.

I am skilled in Praat, R, and ELAN for linguistic data analysis and computational modeling. My research focuses on natural language processing (NLP), large language models (LLMs), and AI-driven language technology, creating innovative solutions for underrepresented languages.

I am passionate about bridging the digital gap, promoting linguistic diversity, and applying data-driven approaches to advance multilingual NLP and AI-powered language solutions.

When I’m not doing linguistics work, I enjoy hiking, microphotography, and making  pizza (pineapple-free!).

Fun Thanksgivingy Linguistics Fact

Why do we say “Turkey”  and not "Americas"?

The name “turkey” is actually a linguistic mistake caused by centuries of trade-route confusion.
In the 1500s, Europeans were already importing a different bird (the guinea fowl) through the Ottoman Empire, which they called the “Turkey bird.”
When Europeans later encountered the wild North American bird, they thought it looked similar and gave it the same name by mistake.
So the American bird inherited the name of a country it has nothing to do with.
In case you were wondering, the following is how the rest of the world calls the American bird:

Across Arabia, they call it "diiq Hindi", which means Indian rooster.

In Russia, it is "Indyushka", meaning bird of India.

In Poland, it is "Indyczka", again meaning bird from India.

In Turkey (the country!), they call it Hindi, which literally means from India.

Sarina R.

Linguist | Bertha Morton Fellowship Recipient(2025-2026)

Sarina Rouhani

Sarina Rouhani is a master's student in Linguistics at the University of Montana, where she works as a course instructor and research assistant in the Linguistics Department. Her research focuses on bilingualism, low-resource languages, natural language processing (NLP), and syntax. She is passionate about language technology, corpus development, and AI-driven solutions for underrepresented languages, striving to bridge the digital gap and ensure linguistic diversity in an AI-powered world.

Sarina aims to pursue a PhD in Linguistics to advance research on computational linguistics, corpus linguistics, and multilingual NLP. 
Outside academia, she enjoys hiking, microphotography, and making pizza (pineapple-free, of course!).

Assoc. Professor at UC Berkeley | Language in humans, animals, and machines

I'm teaching a new class at Berkeley next semester:

Linguistics 265: Biological and Artificial Language

From the syllabus:
This class is an introduction to a novel approach to language. Linguistics has predominantly focused on
human language. 

Recent developments in machine learning and animal communication, however, require us to look beyond the humans. We will extend the definition of language and model it as informative imitation.

The class will introduce a multifaceted approach with human, non-human, and artificial language acting as mutually informative systems. By learning about non human language, we will better understand human language and its uniqueness. 

Vice versa, using linguistic methodology in animal communication and AI can help us gain a better understanding of both artificial and biological language and intelligence.

Computational Linguist and Data Pipeline Expert

Come work with the AI Red-Teaming and Safety Team in the Meta Wearables org! Help us make AI safer! More details in the job posting.
https://lnkd.in/gpGpKbxb

Fun Linguistics Fact

What Are Tokens in AI Language Models?

When we say AI “reads” text, it doesn’t actually process full words like humans do. Instead, it breaks text into tokens, small units that can be whole words, parts of words, or even characters.

For example:

 👉 “Language” might become [“Lan”, “gu”, “age”]
 👉 “I’m happy.” might become [“I”, “’m”, “happy”, “.”]

These tokens are the building blocks LLMs use to learn patterns, predict text, and generate language.
 The way text is tokenized affects how well the model understands meaning, context, and even grammar.

So, next time you see an AI write something surprisingly accurate (or totally off), remember it all starts with tokens!
#AI #Linguistics #NLP #ComputationalLinguistics #MachineLearning #LanguageTechnology #LLM

Amazing Opportunity in Dr. Anoop B J, PhD (Audiology) lab!💯

Assistant Professor at University of Montana

PhD Opportunity in the Brain, Ear, and Aging Research (BEAR) Lab — University of Montana

I’m looking for a motivated and curious PhD student to join my Brain, Ear, and Aging Research (BEAR) Lab at the University of Montana, starting Fall 2026 in the School of Speech, Language, Hearing, and Occupational Sciences.

My lab studies how aging and hearing loss influence auditory processing, cognition, and psychosocial well-being. We use multichannel EEG/ERP, behavioral, and audiological methods to understand how the brain encodes and adapts to complex sound environments. Current projects focus on speech perception in noise, auditory evoked potentials, and brain–behavior relationships in aging.

I’m particularly interested in students with backgrounds in Audiology, Speech and Hearing (Communication Sciences and Disorders), Neuroscience, Psychology, Linguistics, or related fields who are excited about auditory neuroscience, speech perception, psychoacoustics, or neuroimaging.

PhD students will enroll in the PhD in Speech, Language, and Hearing Sciences (SLHS) program at UM. The position includes teaching responsibilities, comprehensive research training, and funding (tuition waiver + annual stipend).
Learn more about the lab:https://lnkd.in/guWVyjfY
PhD Program details: https://lnkd.in/grzeAJTw

If you or someone you know might be interested, feel free to reach out to me at anoop.basavanahallijagadeesh@umt.edu

Linguistics Beneath the waves🐳

To learn more about this project, visit Gasper Begus page!

A new study from UC Berkeley and Project CETI (Cetacean Translation Initiative) started with a whale of a question 🐋. Are whales using elements of human language?

Studies suggest sperm whale calls may be far more complex than previously thought. Featuring vowel-like sounds that resemble elements of human speech.

“In the past, researchers thought of whale communication as a kind of Morse code,” said Berkeley Linguistics Professor Gasper Begus, who is the linguistics lead at Project CETI. “However, this paper shows that their calls are more like very, very slow vowels. This suggests a complexity that approaches human language.”

This breakthrough could transform our understanding of language, animal intelligence, and even legal frameworks for animal rights.

🔗 Learn more about this collaboration between linguists, marine biologists, and AI researchers. https://lnkd.in/gFV_8Zxx

Research Scientist (FAIR) | Linguist

Applications are now open for PhD researchers to visit Meta and collaborate with us as part of the AI Mentorship Program! The program connects PhD students and their advisors with research teams within Meta to do cutting edge AI or ML research.  

To quality you must be a PhD student enrolled at the University of Washington Carnegie Mellon University, University of California, Berkeley, or New York University's Courant Institute of Mathematical Sciences (CIMS) or Center for Data Science (CDS).

You can learn more and apply here: https://lnkd.in/ddzZxVWa

Senior Curriculum Designer at Duolingo

Duolingo is hiring a Director of Learning Design. Message me if you have any questions about the role: https://lnkd.in/eW4gWYhk

Exciting news in BEAR!💯
University of Montana

We have officially begun our EEG experiments in the Brain, Ear, and Aging Research (BEAR) Lab at the University of Montana! A huge thank-you to Brain Products GmbH for their fantastic equipment and support in helping us launch this phase of our research.

Using multichannel EEG, we are now ready to examine how the brain responds to speech sounds, allowing us to explore the neural mechanisms behind age-related changes in hearing, with a special focus on psychosocial wellbeing and cognitive factors in older adults with and without hearing loss.

This is an exciting step toward better understanding how hearing and brain health interact across the lifespan, and toward developing more holistic, evidence-based approaches to supporting healthy aging.
More updates coming soon from the BEAR Lab! 

#EEG #BrainVision #AuditoryNeuroscience #HearingResearch #HealthyAging #Cognition #BEARLab #UniversityOfMontana

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