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Computer Science

D-Index
47
Citations
8141
World Ranking
6546
National Ranking
2893

Overview

Maxine Eskenazi is affiliated with Carnegie Mellon University in the United States. Their research primarily contributes to the field of computer science, with a strong focus on artificial intelligence.

The main research topics covered in their work include:

  • Topic Modeling
  • Speech and dialogue systems
  • Natural Language Processing Techniques
  • AI in Service Interactions
  • Multimodal Machine Learning Applications
  • Multi-Agent Systems and Negotiation
  • Mobile Crowdsensing and Crowdsourcing

They have published extensively, with 50 works classified under computer science and 42 specifically within artificial intelligence. Other areas of study addressed in their publications include computer science applications, computer vision and pattern recognition, information systems, and developmental and educational psychology.

Frequent publication venues by Maxine Eskenazi include:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • Information
  • TIB Data Manager

Notable recent papers are:

  • Overview of the Ninth Dialog System Technology Challenge: DSTC9, 2020, arXiv (Cornell University)
  • Overview of the Ninth Dialog System Technology Challenge: DSTC9, 2024, IEEE/ACM Transactions on Audio Speech and Language Processing
  • Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges, 2022, arXiv (Cornell University)
  • Improving zero and few-shot generalization in dialogue through instruction tuning, 2024, TIB Data Manager
  • Report from the NSF Future Directions Workshop, Toward User-Oriented Agents: Research Directions and Challenges, 2020, arXiv (Cornell University)

Their research collaborations include frequent co-authors such as Shikib Mehri, David Traum, Cathy Jiao, Jeffrey P. Bigham, and Luis Fernando D'Haro.

Best Publications

  • Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders

    Tiancheng Zhao;Ran Zhao;Maxine Eskenazi

  • An overview of spoken language technology for education

    Maxine Eskenazi

  • Let's Go Public! Taking a Spoken Dialog System to the Real World

    Antoine Raux;Brian Langner;Dan Bohus;Alan W. Black

  • Automatic Question Generation for Vocabulary Assessment

    Jonathan Brown;Gwen Frishkoff;Maxine Eskenazi

  • BREF, a large vocabulary spoken corpus for French.

    Lori F. Larnel;Jean-Luc Gauvain;Maxine Eskénazi

  • USING AUTOMATIC SPEECH PROCESSING FOR FOREIGN LANGUAGE PRONUNCIATION TUTORING: SOME ISSUES AND A PROTOTYPE

    Maxine Eskenazi

  • Combining Lexical and Grammatical Features to Improve Readability Measures for First and Second Language Texts

    Michael Heilman;Kevyn Collins-Thompson;Jamie Callan;Maxine Eskenazi

  • Towards End-to-End Learning for Dialog State Tracking and Management using Deep Reinforcement Learning

    Tiancheng Zhao;Maxine Eskenazi

  • An Analysis of Statistical Models and Features for Reading Difficulty Prediction

    Michael Heilman;Kevyn Collins-Thompson;Maxine Eskenazi

  • Doing Research on a Deployed Spoken Dialogue System: One Year of Let's Go! Experience

    Antoine Raux;Dan Bohus;Brian Langner;Alan W. Black

  • Olympus: an open-source framework for conversational spoken language interface research

    Dan Bohus;Antoine Raux;Thomas Harris;Maxine Eskenazi

  • A Finite-State Turn-Taking Model for Spoken Dialog Systems

    Antoine Raux;Maxine Eskenazi

  • Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation

    Tiancheng Zhao;Kyusong Lee;Maxine Eskenazi

  • Trends in speaking styles research

    Maxine Eskénazi

  • USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generation

    Shikib Mehri;Maxine Eskenazi

  • Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models

    Tiancheng Zhao;Kaige Xie;Maxine Eskenazi

  • Crowdsourcing for Speech Processing: Applications to Data Collection, Transcription and Assessment

    Maxine Eskenazi;Gina-Anne Levow;Helen Meng;Gabriel Parent

  • Structured Fusion Networks for Dialog.

    Shikib Mehri;Tejas Srinivasan;Maxine Eskenazi

  • Optimizing Endpointing Thresholds using Dialogue Features in a Spoken Dialogue System

    Antoine Raux;Maxine Eskenazi

  • The 1997 CMU Sphinx-3 English Broadcast News Transcription System

    K. Seymore;S. Chen;S. Doh;M. Eskenazi

Frequent Co-Authors

Alan W. Black
Alan W. Black Carnegie Mellon University
Isabel Trancoso
Isabel Trancoso Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa
David Traum
David Traum University of Southern California
Kevyn Collins-Thompson
Kevyn Collins-Thompson University of Michigan–Ann Arbor
Jamie Callan
Jamie Callan Carnegie Mellon University
Alexander I. Rudnicky
Alexander I. Rudnicky Carnegie Mellon University
Jean-Luc Gauvain
Jean-Luc Gauvain Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur
Louis-Philippe Morency
Louis-Philippe Morency Carnegie Mellon University
Lori Lamel
Lori Lamel University of Paris-Saclay
Diane J. Litman
Diane J. Litman University of Pittsburgh

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