Work at the Intersection of Language and Technology
Computational linguists help machines process human language. All the pioneering language-based technologies in use today — search engines, predictive text messaging, speech recognition, machine translation and voice-user interfaces — rely on the work of computational linguists.
Place yourself at the forefront of this dynamic field by earning a Master of Science in Computational Linguistics at the University of Washington.
Work in Emerging Technologies
Prepare yourself for an exciting career. Computational linguists are in demand in quickly evolving areas such as artificial intelligence and machine learning.
Gain Unique Knowledge
Our program is one of the few that combines the study of linguistics and natural language processing, giving you a unique depth of understanding and skillset for your career.
Get Valuable Experience
Gain hands-on experience through the program's rigorous internships. Our students have interned at some of the world's leading companies, including Amazon and Google.
New Master’s Degree in NLP 2020
Graduate studies in natural language processing at UCSC
NLP scientists in local industry and government
The Executive Director of the Graduate Programme
Adwait Ratnaparkhi has been appointed as executive director of the new master’s degree program in Natural Language Processing.
He is the former director of voice and natural language understanding R&D at Roku and has over 20 years of experience as a researcher and manager at companies such as IBM, Microsoft, Yahoo, and Nuance, and at startups such as 33Across, where he served as chief scientist. During his time at Roku he developed natural language understanding and conversational AI technologies.
Adwait holds a Ph.D. in computer science from the University of Pennsylvania and a B.S.E. in computer science from Princeton University.
Ratnaparkhi foresees a proliferation of smaller, customised voice assistants that will require NLP engineers and programmers.
interdisciplinary master’s in Social Data Science
Computational linguistics is a burgeoning field, and skills are in high-demand in many areas, including speech recognition, artificial intelligence, machine translation, big data, automated text analysis and web search. Brandeis offers three graduate degree programs for students interested in this field.
The two-year Master of Science in Computational Linguistics program is an accessible, intensive two-year curriculum for students who have a linguistics, language, computer science, mathematics, or science background, as well as students without prior study of computer science or linguistics.
The Five-Year BA/MS Program in Computational Linguistics program allows Brandeis BA students to complete the first-year coursework of the two-year Computational Linguistics MS degree during their undergraduate studies.
The Doctor of Philosophy (PhD) in Computer Science program allows students to study computational linguistics while pursuing their doctoral degree.
Graduates of the programs enjoy a very high placement rate in both industry jobs and PhD programs. Our alumni work or have worked in computational linguistics and natural language processing at companies ranging from Adobe, Amazon, Facebook, General Electric, Google, IBM and IBM Watson, and Intuit, to Athena Health, AVOKE, BBN, Basis Technology, Brigham and Women's Hospital, Callminer, Charles River Analytics, Crimson Hexagon, Luminoso, Linguamatics, The MITRE Corporation, Narrative Science, Partners Healthcare, QPID Health, Rakuten, Raytheon, SAP Labs, UFA Inc. and a range of start-ups in the greater metropolitan areas of Boston, New York City, Philadelphia, Chicago and California.
Master of Science in Computational Linguistics
The computational linguistics master's program at Rochester trains students to be conversant both in language analysis and computational techniques applied to natural language. The curriculum consists of courses in linguistics and computer science for a total of 32 credit hours.
Graduates from the computational linguistics program will be prepared for both further training at the PhD level in computer science and linguistics, as well as industry positions. A number companies such as Google, Amazon, Nuance, LexisNexis, and Oracle are searching for employees with advanced degrees in computational linguistics for positions ranging from speech recognition technology to improving translation systems to developing better models of language understanding.
Coursework
The curriculum consists of courses in linguistics and computer science, in roughly a 50/50 mix, for a total of 32 credit hours. Four courses (16 credits) are required in linguistics and four courses (16 credits) in computer science. The degree also requires a culminating special written project on a topic relevant to the student's interest and in consultation with individual advisors.
This program’s coursework can typically be completed in three full-time semesters. A fourth semester is for students to prepare their program’s final assignment, project, or thesis.
Linguistics Courses
Prerequisite
Students are required to have completed the following prerequisite course, or its equivalent.
LING 110: Introduction to Linguistic Analysis
Track Courses
Within linguistics, students will work with an advisor to create a “track” for their coursework in one of three areas:
Sound structure (LING 410, 427, 510)
Grammatical structure (LING 420, 460, 461, 462, 520)
Meaning (LING 425, 465, 466, 468, 525, 535)
Students will be encouraged to take LING 450 and LING 501 as it suits their programs.
Required
At least one of the following:
LING 410: Introduction to Language Sound Systems
LING 420: Introduction to Grammatical Systems
LING 425: Introduction to Semantic Analysis
Plus at least two from the following:
LING 427: Topics in Phonetics and Phonology
LING 450: Data Science for Linguistics
LING 460: Syntactic Theory
LING 461: Phrase Structure Grammar
LING 462: Topics in Experimental Syntax
LING 465: Formal Semantics
LING 466: Pragmatics
LING 468: Computational Semantics
LING 481: Statistical and Neural Computational Linguistics
LING 501: Linguistics Graduate Proseminar
LING 520: Syntax
LING 525: Graduate Semantics
LING 527: Topics in Phonetics and Phonology
LING 535: Formal Pragmatics
Computer Science Courses
Prerequisites
Students are required to have completed the following prerequisite courses, or its equivalents:
CSC 171: The Science of Programming
CSC 172: The Science of Data Structures
CSC 173: Computation and Formal Systems
MATH 150: Discrete Math
MATH 165: Linear Algebra with Differential Equations
Required
Students must take two of the following three courses for the MS in Computational Linguistics.
LING 424: Introduction to Computational Linguistics
CSC 447: Natural Language Processing
CSC 448: Statistical Speech and Language Processing
Plus at least two of the following:
CSC 440: Data Mining
CSC 442: Artificial Intelligence
CSC 444: Logical Foundations of Artificial Intelligence
CSC 446: Machine Learning
Introduction
What is computational linguistics? The Association for Computational Linguistics (ACL) describes computational linguistics as the scientific study of language from a computational perspective. Computational linguists provide computational models of various types of linguistic phenomena.
Computational linguistics (CL) combines resources from linguistics and computer science to discover how human language works.
Computational linguistics is a field of vital importance in the information age. Computational linguists create tools for important practical tasks such as machine translation, speech recognition, speech synthesis, information extraction from text, grammar checking, text mining and more.
Computational Linguistics Graduate Programs
The major schools in computational linguistics typically have a strong interdisciplinary culture with the linguistics department and the computer science department and with other related departments.
Where do you get a graduate degree with a specialization in computational linguistics? Some linguistics departments offer the specialization, however at many colleges and universities the computer science (CS) department or a related department actually offers the specialization. Some computer science departments don’t even mention a computational linguistics specialization at their website, however they actually have computer science graduate students specializing in computational linguistics along with faculty members performing research in the subject. Upon request the CS departments typically allow qualified graduate students to focus on CL.
Computational linguistic students study subjects such as semantics, computational semantics, syntax, models in cognitive science, natural language processing systems and applications, morphology, linguistic phonetics and phonology.
Students may also study sociolinguistics, psycholinguistics, corpus linguistics, machine learning, applied text analysis, grounded models of meaning, data-intensive computing for text analysis, and information retrieval.
During their journey computational linguistic students typically take computer programming courses as well as math and statistics courses. However, some general courses such as methods in computational linguistics teach computer programming at a level which provides students the skills to begin creating computer applications to address computational linguistics tasks. Some Ph.D. programs require students to have a proficiency in discrete mathematics or mathematical linguistics.
Ph.D. students specializing in CL in the computer science department can take courses such as operating systems, programming languages, analysis of algorithms, natural language processing, computation and formal systems, science of data structures, machine learning, artificial intelligence, and computer architecture.
Computational Linguistics Careers
Computational linguistics is the most commercially viable branch of linguistics; hundreds of companies in the United States work on computational linguistics. Computational linguists work for high tech companies, creating and testing models for improving or developing new software in areas such as speech recognition, grammar checkers, dictionary development and more. Computational linguists also work in the areas of computer-mediated language learning and artificial intelligence. They also work in research groups at universities and government research labs.
Some of the companies which employ computational linguists include:
Alelo
Apple
Expert System
Facebook
Google
Intel
Lingsoft
Lionbridge
Microsoft
North Side
Nuance
Oracle
SDL
Sensory
SRI STAR laboratory
Systran
Vantage Linguistics
VoiceWeb
Yahoo
Natural Language Processing
The computational linguistics and the natural language communities overlap. The methodologies of computational linguistics and natural language processing (NLP) are often related. Computational linguistics and natural language processing make use of formal training in linguistics, computer sciences and machine learning.
NLP allows computers to understand, analyze, and derive meaning from human language in an intelligent and useful way. NLP professionals organize and structure knowledge to perform tasks such as translation, relationship extraction, automatic summarization, sentiment analysis, text clustering and categorization, named entity recognition, text segmentation and speech recognition.
NPL systems, with their ability to analyze language for its meaning, have filled roles such as correcting grammar, automatically translating between languages, and converting speech to text.
Cognitive computing uses natural language processing in a variety of ways. Natural language processing provides a way for machines to communicate with people on conventional language-based terms, which makes NLP an important factor in cognitive computing.
Data scientist use natural language processing for log analysis of security models, risk management and regulatory compliance as well as price and demand forecasting.
Companies use NLP to improve the accuracy of documentation, improve the efficiency of documentation processes, and to identify the most pertinent information from large databases.
Natural language processing and text analytics are major factors in search and its numerous Internet-based applications. Companies use NLP in sentiment analysis of social media.
Contribute to one of the fastest-growing sectors!
Speech technologies have permeated modern life so much that we hardly even notice their presence, much less understand how they work. Whenever you dictate a message on your smartphone, ask Alexa the weather, use instant translation software, or learn a language using an app, you are using voice technologies. And with new Internet-of-Things applications on the horizon, smart spaces and the presence of Siri, Alexa, Cortana, Bixby and Google Home are poised to grow even further. Voice technologies are a multibillion-dollar industry with potential for unparalleled social and scientific impact.
Innovate, explore, create!
This programme is very hands-on. You will get your hands dirty working in teams making synthetic voices, speech recognizers, and more. You’ll even make your own voice-tech demo. People with scientific expertise in the domain of voice technology are in short supply. We aim to fix that. Starting with you! In this one-year programme, you will join cutting-edge scholars, professionals, and technologists working at the forefront of voice technology innovation.
Join the forefront of technological innovation!
Just as the smartphone ushered in a new wave of innovation, forever changing how we communicate, engage, navigate, and shop, so too is voice technology poised to fundamentally alter how we interact with our ubiquitous, interconnected devices.
A totally unique Master’s programme!
This Master’s programme is a one-of-its-kind. No other Master’s programme in continental Europe is dedicated exclusively to Voice Technology. No matter if your Bachelor’s degree is in linguistics, computer science, engineering, digital humanities, or something else altogether, if you are interested in voice technology and aren’t afraid of exploring new terrain, then this is the programme for you.
If you are interested in challenges relating to:
synthetic voices and speech recognition
the interplay between voice, language, speech and technology
tools to support lesser-resourced minoritized languages
radical innovation around voice forensics, including topics like accent recognition, intoxication detection, real-time speech pathology analysis, etc.
ethical issues relating to voice technology
then join us at the University of Groningen (Campus Fryslân) MSc Voice Technology.
Job prospects
Considering the numbers for the sectors ICT and linguistics, estimations are that people working in ICT and specifically application developers have remarkably positive career perspectives. These estimates are also reflected in the rapidly growing international market for voice assistants, smart speakers, and countless other IoT-connected devices enabled with voice technology.
Considering only the case for the Netherlands, after the introduction of Dutch-enabled smart speakers in 2018, the market for these products grew from 0% to 5% in under five months! The trend continues upward. Overall, the career perspectives for graduates from the Voice Technology MSc. are remarkably positive.
In designing this programme, we interview many Dutch speech technology companies. All of them have difficulties fulfilling local vacancies and remarked on the paucity of applicants with the requisite combination of linguistic knowledge, programming skills and experience with machine learning, all of which are core to the MSc Voice Technology.
Job examples
Speech Scientist
Speech Analyst
Research Engineer
Language Data Specialist
Voice Forensic Specialist
Entrepreneur
Various research and academic careers as a PhD student at several universities or academic speech technology labs in Europe and beyond!
Research
Culture, Language & Technology Flagship
The Culture, Language & Technology Flagship comprises an interdisciplinary team of doctoral researchers and lecturers who are dedicated to exploring how Human, Social and Behavioural Science-lead research can have a regional impact. The Flagship has two research themes:
Minoritized languages and multilingualism: Much scholarly activity at the CLT Flagship (including all PhD research) involves work on Frisian and Dutch minority cultures and languages alongside other minoritized cultures and languages.
Voice and speech technologies: Research is dedicated to voice and speech technologies. This theme includes not only technological components, but also social and cultural issues (e.g. how technology is used, by whom, and for what purposes)
Students in the MSc Voice Technology. may have the opportunity to collaborate on doctoral research, build up an international network and participate in periodic lectures, summer schools and events organized by the Culture, Language & Technology Flagship.
Computational linguistics graduate programs ranking guidelines:
We selected the graduate programs based on the quality of the program, types of courses provided, research opportunities, and faculty strength including research, awards, recognition and reputation. We also received advice from professors in the computational linguistics field.
Just as the smartphone ushered in a new wave of innovation, forever changing how we communicate, engage, navigate, and shop, so too is voice technology poised to fundamentally alter how we interact with our ubiquitous, interconnected devices
How do we cope with the information overload of modern media? What is the best way to collect data in a multilingual environment? Find out in this international Double Degree track.
The track in Language and Communication Technologies combines Theoretical Linguistics and Computer Science. You will study language technology in a multi-lingual setting.
The two-year training is part of the prestigious international Erasmus Mundus program. The first year you will start in Groningen. You will finish the program with a stay at one of our partner universities in the second year. After completing the track, you will receive two Master's degrees: a degree in Linguistics in Groningen and a second Master's degree depending on the partner university you chose to stay at.
The program consists of compulsory and optional courses. In this way, you can design the program o fit your interests. In addition, you will do a research project and write a Master's thesis.
Language and Communication Technologies is an Erasmus Mundus program.
Why study this program in Groningen?
Erasmus Mundus Master's Program.
A unique combination of theoretical linguistics and computer-science research in a multi-lingual setting.
A rapidly evolving area of study with excellent career opportunities, both in industry and academia.
Bachelor's diploma in a field related to Computer Science, Theoretical Linguistics, Artificial Intelligence.
The Association for Computational Linguistics describes computational linguistics as the scientific study of language from a computational perspective.
Computational linguistics (CL) combines resources from linguistics and computer science to discover how human language works. Computational linguists create tools for critical tasks such as machine translation, speech recognition, speech synthesis, grammar checking, and text mining.
Typically, computer science (CS) departments at colleges and universities offer computational linguistics as a specialization, though some linguistics departments also offer it. Some CS departments don't offer CL as a formal specialization, but qualified students can often work with faculty to create their own focus area.
Computational linguistics graduate students take computer programming, math, and statistics courses. They examine subjects such as semantics, computational semantics, natural language processing, models in cognitive science, and phonology.
A top-ranked private institution focused on technology, the Massachusetts Institute of Technology offers a doctorate in linguistics that lets students design their own focus area
At Stanford University, the Stanford Natural Language Processing (NLP) Group brings together faculty and graduate students in linguistics and computer science to advance the science of computer processing of human languages. Members of the group conduct research on computational linguistics,...
At Harvard University, graduate students can pursue a focus in computational linguistics through graduate programs in applied computation. The Institute for Applied Computational Science comprises graduate students and faculty focused on applied computational methods, including computational linguistics.
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The Departments of Linguistics and Computer Science and Engineering jointly participate in a Master of Science in Computational Linguistics. The mission of the program is to prepare students for a career in the Human Language Technologies industry. This program is on the STEM OPT extension list (CIP number 30.1801). If you are a current UB Linguistics PhD student interested in pursuing the MS as well, please view the PhD Applicants to MS page.
There are currently eight students in the MS program, two of which are also pursuing a PhD in Linguistics.
Student spotlight
MS graduate Xuejiao Chen accepted this Spring of 2020 a position as an assistant NLP Engineer at the Institute of Information Science of the China Electronics Technology Group Corporation.
MS graduate Soo Hyun Ryu has been accepted to the Psychology program at Michigan University, starting Fall 2020.
MS graduates Mengyang-Qiu and Xuejiao Chen have turned a term paper into a published conference paper: Qiu, M., Chen, X., Liu, M., Parvathala, K., Patil, A. & Park, J. (2019) "Improving precision of grammatical error correction with a cheat sheet", in Proceedings of the 14th Workshop on Innovative Use of NLP for Building Educational Applications, collocated with the 2019 ACL Conference.
MS student Soo Hyun Ryu will graduate in the Spring of 2019 and will be working as a researcher in the NLP*CL Lab at Korea Advanced Institute for Science and Technology (KAIST) as well as a Grammar Developer for Lionbridge.
MS student Soo Hyun Ryu presented a paper entitled "On the interaction between dependency frequency and thematic fit in sentence processingDownload pdf" at the 2019 Annual Meeting of the Society for Computation in Linguistics, NYC.
MS/PhD student Erika Bellingham completed an internship at Google, as an Analytical Linguist Intern (Intent Schema Team) from June 2018 to August 2018. She worked on natural language systems for the Google Assistant, and used linguistic analysis to improve Natural Language Understanding and Natural Language Generation systems.
MS/PhD student Hao Sun has graduated in the Spring of 2018, and was hired as an Artificial Intelligence Scientist by Astound, AI., a startup located in Menlo Park, California.
MS student Dianna Radpour took a leave during the Spring of 2018 to participate in an internship in the Reiken Institute (Tokyo, Japan). In the Fall of 2018 she graduated, and moved on to a PhD program at the University Colorado.
MS students are encouraged to seek internships they are interested in via Bullseye, or to participate in our local internship in the Natural Language Understanding Laboratory at the Department of Biomedical Sciences
The Stanford NLP Group is always on the lookout for budding new computational linguists. Stanford has a great program at the cutting edge of modern computational linguistics.
The best way to get a sense of what goes on in the NLP Group is to look at our research blog, publications, and students' and faculty's homepages. Our research centers around using probabilistic and other machine learning methods over rich linguistic representations in a variety of languages. The group is small, but productive and scientifically focused.