H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 37 Citations 6,158 128 World Ranking 5293 National Ranking 2603

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Natural language processing
  • Programming language

Her main research concerns Artificial intelligence, Natural language processing, Dialog box, Speech recognition and Human–computer interaction. Her Artificial intelligence research includes elements of Ordinal regression, Interface and Set. Her Natural language processing study incorporates themes from Spoken dialog, Vocabulary, Readability and Reading.

Dialog box is often connected to Machine learning in her work. Her research in Speech recognition tackles topics such as Spoken dialog systems which are related to areas like Control, Word error rate and Variation. Her research investigates the connection between Human–computer interaction and topics such as Dialog system that intersect with problems in Control and Speech technology.

Her most cited work include:

  • Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders (345 citations)
  • An overview of spoken language technology for education (194 citations)
  • Automatic Question Generation for Vocabulary Assessment (192 citations)

What are the main themes of her work throughout her whole career to date?

Her primary scientific interests are in Artificial intelligence, Natural language processing, Dialog box, Speech recognition and Vocabulary. As part of the same scientific family, Maxine Eskenazi usually focuses on Artificial intelligence, concentrating on Domain and intersecting with Set. Her Natural language processing research focuses on Context and how it relates to Feature learning.

As part of one scientific family, Maxine Eskenazi deals mainly with the area of Dialog box, narrowing it down to issues related to the Human–computer interaction, and often Crowdsourcing. Her Speech recognition study integrates concerns from other disciplines, such as Pronunciation and Transcription. Her Vocabulary study combines topics from a wide range of disciplines, such as TUTOR, Information retrieval and Reading.

She most often published in these fields:

  • Artificial intelligence (55.98%)
  • Natural language processing (43.48%)
  • Dialog box (28.80%)

What were the highlights of her more recent work (between 2017-2021)?

  • Artificial intelligence (55.98%)
  • Dialog box (28.80%)
  • Natural language processing (43.48%)

In recent papers she was focusing on the following fields of study:

Maxine Eskenazi mainly focuses on Artificial intelligence, Dialog box, Natural language processing, Machine learning and Human–computer interaction. Her Artificial intelligence research incorporates themes from Graph and Vocabulary. In general Dialog box study, her work on Dialog system often relates to the realm of Judgement, thereby connecting several areas of interest.

Her Natural language processing research includes themes of Context, Representation, Control and Granularity. Her work on Reinforcement learning as part of her general Machine learning study is frequently connected to Open domain and Quality, thereby bridging the divide between different branches of science. Maxine Eskenazi has researched Human–computer interaction in several fields, including Spoken dialog systems and Turing.

Between 2017 and 2021, her most popular works were:

  • Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation (91 citations)
  • Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models (53 citations)
  • Pretraining Methods for Dialog Context Representation Learning (27 citations)

In her most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Programming language
  • Machine learning

Maxine Eskenazi spends much of her time researching Dialog box, Artificial intelligence, Machine learning, Natural language processing and Reinforcement learning. As a part of the same scientific study, Maxine Eskenazi usually deals with the Dialog box, concentrating on Feature learning and frequently concerns with Context. Artificial intelligence is closely attributed to Measure in her work.

The various areas that Maxine Eskenazi examines in her Robustness study include Fusion and Generative model. Her Semantics research is multidisciplinary, incorporating elements of Space, Embedding, Dialog system, Matching and Generative grammar. Process overlaps with fields such as Vocabulary, Inference and Latent variable in her research.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

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

Tiancheng Zhao;Ran Zhao;Maxine Eskenazi.
meeting of the association for computational linguistics (2017)

345 Citations

An overview of spoken language technology for education

Maxine Eskenazi.
Speech Communication (2009)

331 Citations

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

Antoine Raux;Brian Langner;Dan Bohus;Alan W. Black.
conference of the international speech communication association (2005)

304 Citations

BREF, a large vocabulary spoken corpus for French.

Lori F. Larnel;Jean-Luc Gauvain;Maxine Eskénazi.
conference of the international speech communication association (1991)

295 Citations

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

Maxine Eskenazi.
Language Learning & Technology (1999)

269 Citations

Automatic Question Generation for Vocabulary Assessment

Jonathan Brown;Gwen Frishkoff;Maxine Eskenazi.
empirical methods in natural language processing (2005)

266 Citations

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

Michael Heilman;Kevyn Collins-Thompson;Jamie Callan;Maxine Eskenazi.
north american chapter of the association for computational linguistics (2007)

247 Citations

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

Dan Bohus;Antoine Raux;Thomas Harris;Maxine Eskenazi.
north american chapter of the association for computational linguistics (2007)

167 Citations

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

Antoine Raux;Dan Bohus;Brian Langner;Alan W. Black.
conference of the international speech communication association (2006)

165 Citations

An Analysis of Statistical Models and Features for Reading Difficulty Prediction

Michael Heilman;Kevyn Collins-Thompson;Maxine Eskenazi.
workshop on innovative use of nlp for building educational applications (2008)

165 Citations

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