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Computer Science

D-Index
41
Citations
6660
World Ranking
8886
National Ranking
3782

Overview

Brian Roark is affiliated with Google in the United States. Their body of work primarily spans the field of Computer Science, with a significant focus on Artificial Intelligence, Language and Linguistics, Computer Vision and Pattern Recognition, Signal Processing, and Cultural Studies.

The scientist's research topics include:

  • Natural Language Processing Techniques
  • Topic Modeling
  • Handwritten Text Recognition Techniques
  • Translation Studies and Practices
  • Text Readability and Simplification
  • Language and cultural evolution
  • Authorship Attribution and Profiling

Brian Roark has contributed to a number of recent papers. These works include:

  • Phonotactic Complexity and Its Trade-offs, 2020, Repository for Publications and Research Data (ETH Zurich)
  • Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset, 2020, arXiv (Cornell University)
  • Context-aware Transliteration of Romanized South Asian Languages, 2023, Computational Linguistics
  • Graphemic Normalization of the Perso-Arabic Script, 2022, arXiv (Cornell University)

These publications appear extensively in venues such as arXiv (Cornell University), Computational Linguistics, and the Repository for Publications and Research Data (ETH Zurich). The frequency of publications across these venues includes:

  • arXiv (Cornell University): 8 publications
  • Computational Linguistics: 2 publications
  • Repository for Publications and Research Data (ETH Zurich): 1 publication
  • Grapholinguistics and its applications: 1 publication

The scientist frequently collaborates with peers including Christo Kirov, Cibu Johny, Alexander Gutkin, Raiomond Doctor, and Richard Sproat.

Best Publications

  • Incremental Parsing with the Perceptron Algorithm

    Michael Collins;Brian Roark

  • Probabilistic top-down parsing and language modeling

    Brian Roark

  • Spoken Language Derived Measures for Detecting Mild Cognitive Impairment

    B. Roark;M. Mitchell;J. Hosom;K. Hollingshead

  • Discriminative n-gram language modeling

    Brian Roark;Murat Saraclar;Michael Collins

  • Noun-Phrase Co-occurrence Statistics for Semi-Automatic Semantic Lexicon Construction

    Brian Roark;Eugene Charniak

  • Deriving lexical and syntactic expectation-based measures for psycholinguistic modeling via incremental top-down parsing

    Brian Roark;Asaf Bachrach;Carlos Cardenas;Christophe Pallier

  • Unsupervised language model adaptation

    M. Bacchiani;B. Roark

  • Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm

    Brian Roark;Murat Saraclar;Michael Collins;Mark Johnson

  • Generalized Algorithms for Constructing Statistical Language Models

    Cyril Allauzen;Mehryar Mohri;Brian Roark

  • The SRI/OGI 2006 spoken term detection system.

    Dimitra Vergyri;Izhak Shafran;Andreas Stolcke;Venkata Ramana Rao Gadde

  • RSVP keyboard: An EEG based typing interface

    Umut Orhan;Kenneth E. Hild;Deniz Erdogmus;Brian Roark

  • The OpenGrm open-source finite-state grammar software libraries

    Brian Roark;Richard Sproat;Cyril Allauzen;Michael Riley

  • Discriminative Syntactic Language Modeling for Speech Recognition

    Michael Collins;Brian Roark;Murat Saraclar

  • Supervised and unsupervised PCFG adaptation to novel domains

    Brian Roark;Michiel Bacchiani

  • Syntactic complexity measures for detecting Mild Cognitive Impairment

    Brian Roark;Margaret Mitchell;Kristy Hollingshead

  • Phonotactic Complexity and Its Trade-offs

    Tiago Pimentel;Brian Roark;Ryan D. Cotterell

  • Bringing Contextual Information to Google Speech Recognition

    Petar S. Aleksic;Mohammadreza Ghodsi;Assaf Hurwitz Michaely;Cyril Allauzen

  • What Kind of Language Is Hard to Language-Model?

    Sebastian J. Mielke;Ryan Cotterell;Kyle Gorman;Brian Roark

  • MAP adaptation of stochastic grammars

    Michiel Bacchiani;Michael Riley;Brian Roark;Richard Sproat

  • Brain–Computer Interface With Language Model–Electroencephalography Fusion for Locked-In Syndrome

    Barry S. Oken;Umut Orhan;Brian Roark;Deniz Erdogmus

  • Fully Automated Neuropsychological Assessment for Detecting Mild Cognitive Impairment.

    Maider Lehr;Emily Tucker Prud'hommeaux;Izhak Shafran;Brian Roark

  • Neural models of text normalization for speech applications

    Hao Zhang;Richard Sproat;Axel H. Ng;Felix Stahlberg

Frequent Co-Authors

Murat Saraclar
Murat Saraclar Boğaziçi University
Ryan Cotterell
Ryan Cotterell ETH Zurich
Richard Sproat
Richard Sproat Google (United States)
Deniz Erdogmus
Deniz Erdogmus Northeastern University
Barry Oken
Barry Oken Oregon Health & Science University
Michael Riley
Michael Riley Google (United States)
Sanjeev Khudanpur
Sanjeev Khudanpur Johns Hopkins University
Mark Johnson
Mark Johnson Macquarie University
Eugene Charniak
Eugene Charniak Brown University
Jason Eisner
Jason Eisner Johns Hopkins University

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