World's Best Scientists 2026 revealed!

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Computer Science

D-Index
53
Citations
13735
World Ranking
4752
National Ranking
2208

Overview

Karen Livescu is affiliated with the Toyota Technological Institute at Chicago in the United States. Their research primarily spans the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Signal Processing, Human-Computer Interaction, Developmental and Educational Psychology, and Computer Vision and Pattern Recognition.

The main topics covered in their work include Speech Recognition and Synthesis, Natural Language Processing Techniques, Topic Modeling, Music and Audio Processing, Hand Gesture Recognition Systems, Speech and Audio Processing, and Hearing Impairment and Communication.

Livescu has published extensively, with notable papers including:

  • "Self-Supervised Speech Representation Learning: A Review", 2022, IEEE Journal of Selected Topics in Signal Processing
  • "What Do Self-Supervised Speech Models Know About Words?", 2024, Transactions of the Association for Computational Linguistics
  • "Layer-Wise Analysis of a Self-Supervised Speech Representation Model", 2021, 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)
  • "Chess as a Testbed for Language Model State Tracking", 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • "A Correspondence Variational Autoencoder for Unsupervised Acoustic Word Embeddings", 2020, arXiv (Cornell University)

Their frequent coauthors include the following researchers:

  • Shinji Watanabe
  • Ankita Pasad
  • Suwon Shon
  • Hung-yi Lee
  • Kevin Gimpel

Livescu's work has appeared repeatedly in certain publication venues, notably:

  • arXiv (Cornell University)
  • IEEE Journal of Selected Topics in Signal Processing
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Transactions of the Association for Computational Linguistics
  • 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)

Best Publications

  • Deep Canonical Correlation Analysis

    Galen Andrew;Raman Arora;Jeff Bilmes;Karen Livescu

  • Multi-view clustering via canonical correlation analysis

    Kamalika Chaudhuri;Sham M. Kakade;Karen Livescu;Karthik Sridharan

  • On Deep Multi-View Representation Learning

    Weiran Wang;Raman Arora;Karen Livescu;Jeff Bilmes

  • Towards Universal Paraphrastic Sentence Embeddings

    John Wieting;Mohit Bansal;Kevin Gimpel;Karen Livescu

  • Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2007 (ICASSP 2007)

    K. Livescu;A. Bezman;N. Borges;L. Yung

  • Self-Supervised Speech Representation Learning: A Review

    Unknown

  • Tailoring Continuous Word Representations for Dependency Parsing

    Mohit Bansal;Kevin Gimpel;Karen Livescu

  • From Paraphrase Database to Compositional Paraphrase Model and Back

    John Wieting;Mohit Bansal;Kevin Gimpel;Karen Livescu

  • Speech production knowledge in automatic speech recognition.

    Simon King;Joe Frankel;Karen Livescu;Erik McDermott

  • Charagram: Embedding Words and Sentences via Character n-grams

    John Wieting;Mohit Bansal;Kevin Gimpel;Karen Livescu

  • Stochastic optimization for PCA and PLS

    Raman Arora;Andrew Cotter;Karen Livescu;Nathan Srebro

  • Pre-training on high-resource speech recognition improves low-resource speech-to-text translation

    Sameer Bansal;Herman Kamper;Karen Livescu;Adam Lopez

  • Deep convolutional acoustic word embeddings using word-pair side information

    Herman Kamper;Weiran Wang;Karen Livescu

  • Deep Multilingual Correlation for Improved Word Embeddings

    Ang Lu;Weiran Wang;Mohit Bansal;Kevin Gimpel

  • Unsupervised learning of acoustic features via deep canonical correlation analysis

    Weiran Wang;Raman Arora;Karen Livescu;Jeff A. Bilmes

  • Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

    David Yarowsky;Timothy Baldwin;Anna Korhonen;Karen Livescu

  • A Comparison of Techniques for Language Model Integration in Encoder-Decoder Speech Recognition

    Shubham Toshniwal;Anjuli Kannan;Chung-Cheng Chiu;Yonghui Wu

  • Articulatory Feature-Based Methods for Acoustic and Audio-Visual Speech Recognition: Summary from the 2006 JHU Summer workshop

    K. Livescu;O. Cetin;M. Hasegawa-Johnson;S. King

  • Landmark-based speech recognition: report of the 2004 Johns Hopkins summer workshop

    M. Hasegawa-Johnson;J. Baker;S. Borys;K. Chen

  • Fixed-dimensional acoustic embeddings of variable-length segments in low-resource settings

    Keith Levin;Katharine Henry;Aren Jansen;Karen Livescu

  • Deep Variational Canonical Correlation Analysis

    Weiran Wang;Honglak Lee;Karen Livescu

Frequent Co-Authors

Kevin Gimpel
Kevin Gimpel Toyota Technological Institute at Chicago
Mohit Bansal
Mohit Bansal University of North Carolina at Chapel Hill
Gregory Shakhnarovich
Gregory Shakhnarovich Toyota Technological Institute at Chicago
Jeff A. Bilmes
Jeff A. Bilmes University of Washington
Diane Brentari
Diane Brentari University of Chicago
Sharon Goldwater
Sharon Goldwater University of Edinburgh
Kate Saenko
Kate Saenko Boston University
Mark Hasegawa-Johnson
Mark Hasegawa-Johnson University of Illinois at Urbana-Champaign
Mari Ostendorf
Mari Ostendorf University of Washington

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