Adam Albright

About

Adam Albright is a Professor of Linguistics at the Massachusetts Institute of Technology. His research interests include phonology, morphology, language acquisition, and computational linguistics. He has contributed to the understanding of inflectional paradigms, analogy in grammar, and the morphological basis of paradigm leveling, with publications exploring language universals, language change, and the identification of bases in morphological paradigms. His work often involves analyzing language data such as Yiddish, Korean, and Spanish, and he has been involved in advancing theoretical models related to language structure and change.

Research topics

• Computer Science
• Artificial Intelligence
• Natural Language Processing
• Data science
• Mathematics
• Biology
• Computational biology
• Linguistics

Selected publications

• Feature-based generalisation as a source of gradient acceptability

  Phonology · 2009-05-01 · 178 citations

  article1st authorCorresponding

  Abstract Phonological judgements are often gradient: blick >? bwick >* bnick >** bzick . The mechanisms behind gradient generalisation remain controversial, however. This paper tests the role of phonological features in helping speakers evaluate which novel combinations receive greater lexical support. A model is proposed in which the acceptability of a string is based on the most probable combination of natural classes that it instantiates. The model is tested on its ability to predict…

  PublisherDOI

• 7 Explaining Universal Tendencies and Language Particulars in Analogical Change

  2008-01-24 · 119 citations

  book-chapter1st authorCorresponding

  Abstract This chapter shows that a confidence-based model can make correct predictions not only about individual cases, but also about the typology of analogical change. The chapter is organized as follows: first, it provides a brief overview of tendency-based vs. structurally-based approaches to analogical change, summarizing the major generalizations that have been uncovered, and situating the current work in an area that has been approached from radically different perspectives. It then prese…

  PublisherDOI

• 9 Modeling analogy as probabilistic grammar

  2009-07-30 · 93 citations

  book-chapter1st authorCorresponding

  Abstract Models of analogy must be non-deterministic enough to handle gradient data, but must also explain why analogy obeys some striking restrictions: only a tiny subset of logically possible analogies are actually attested. This chapter discusses several unattested types of analogy, and considers their implications for formal models. Gradience and notable restrictions are best modeled using a grammar of probabilistic rules.

  PublisherDOI

• Base-driven leveling in Yiddish verb paradigms

  Natural Language & Linguistic Theory · 2010-08-01 · 81 citations

  article1st authorCorresponding
  PublisherDOI

• Learning and Learnability in Phonology

  2011-09-16 · 52 citations

  otherOpen access1st authorCorresponding

  This chapter contains sections titled: Chapter Content Defining the Problem Learning Phonotactics Phonological Alternations What Doesn't Have to be Learned? The Issue of UG Conclusion

  PublisherOA PDFDOI

Frequent coauthors

• Bruce Hayes

  University of California, Los Angeles

  13 shared

• Douglas C. Schmidt

  Vanderbilt University

  4 shared

• Jules White

  Vanderbilt University

  4 shared

• Richard Futrell

  4 shared

• Brian Dougherty

  National Institute of Standards and Technology

  4 shared

• Chris Thompson

  Oconee Fall Line Technical College

  4 shared

• Giorgio Magri

  3 shared

• Timothy J. O’Donnell

  3 shared

Labs

• MIT Linguistics Reading Groups and LabsPI

Similar researchers at Massachusetts Institute of Technology

• David Pesetskyh-26
• Allan Doyleh-1