About
Steven Abney's area of research is computational linguistics, which encompasses language technology (machine translation, speech recognition, information extraction), digital linguistics, the language part of artificial intelligence, and computational psycholinguistics. His career has alternated between academic linguistic departments and computer science departments in industrial research labs. To his mind, language is an intrinsically computational system, and computational linguistics is linguistics. Languages are no less complex than subatomic particles, galaxies, or living cells, and they deserve to be studied with the kind of mathematical and computational sophistication that is taken for granted in physics, astronomy, or molecular biology.
The projects he is currently working on include language digitization, low-resource computational linguistics, digital documentation of Ojibwe, semantic interpretation, dynamic semantics and improper anaphora. Other projects he has worked on include dependency parsing, semisupervised learning and spectral methods, information extraction, especially for biomed, partial parsing and deterministic parsing, grammatical inference, conversational agents, spoken language systems, automated phonetic transcription, and automated harmonic analysis of music.
Courses he teaches include Mathematics of Language (Ling 341), Computational Linguistics (Ling 441), Machine Learning for NLP (Cogsci/Ling 445), and the undergraduate and graduate introductions to semantics (Ling 316, 516).
Affiliation(s)
- Linguistics
- Computer Science and Engineering affiliate
- Michigan Institute for Data Science affiliate
Field(s) of Study
- Computational linguistics, especially parsing and semi-supervised learning, language documentation, semantics
