D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 30 Citations 4,432 139 World Ranking 8708 National Ranking 14

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His main research concerns Artificial intelligence, Speech recognition, Natural language processing, Language model and Word. His study in Word error rate and Perceptron are all subfields of Artificial intelligence. His work carried out in the field of Perceptron brings together such families of science as Parsing and Pattern recognition.

His Speech recognition study combines topics from a wide range of disciplines, such as Vocabulary and Search engine indexing. Murat Saraclar combines subjects such as Pronunciation, Agglutinative language, Turkish and Decision tree with his study of Natural language processing. As part of his studies on Language model, Murat Saraclar frequently links adjacent subjects like Discriminative model.

His most cited work include:

  • Lattice-Based Search for Spoken Utterance Retrieval (230 citations)
  • Discriminative n-gram language modeling (173 citations)
  • System and Method of Lattice-Based Search for Spoken Utterance Retrieval (165 citations)

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

Murat Saraclar focuses on Artificial intelligence, Speech recognition, Natural language processing, Language model and Pattern recognition. His Artificial intelligence research is multidisciplinary, relying on both Keyword search and Vocabulary. His Speech recognition research includes themes of Transcription and Search engine indexing.

His research in Natural language processing intersects with topics in Pronunciation, Agglutinative language and Turkish. His Language model research is multidisciplinary, incorporating elements of Syntax, Discriminative model, Perceptron and Natural language. His work on Mixture model and Support vector machine as part of his general Pattern recognition study is frequently connected to Gaussian process, thereby bridging the divide between different branches of science.

He most often published in these fields:

  • Artificial intelligence (72.07%)
  • Speech recognition (59.22%)
  • Natural language processing (47.49%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (72.07%)
  • Natural language processing (47.49%)
  • Sign language (7.82%)

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

Murat Saraclar mainly investigates Artificial intelligence, Natural language processing, Sign language, Speech recognition and Sign. Murat Saraclar interconnects Machine learning, Multivariate statistics, Autoregressive model, Stethoscope and Pattern recognition in the investigation of issues within Artificial intelligence. His studies deal with areas such as Annotation, Embedding and Context model as well as Natural language processing.

The study incorporates disciplines such as Keyword search and Speech processing in addition to Sign language. His Dynamic time warping study in the realm of Speech recognition connects with subjects such as Frame. His Word research is multidisciplinary, incorporating perspectives in Hidden Markov model and Word error rate.

Between 2018 and 2021, his most popular works were:

  • Question Answering for Spoken Lecture Processing (9 citations)
  • Low Resource Keyword Search With Synthesized Crosslingual Exemplars (4 citations)
  • Turkish Natural Language Processing (3 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of investigation include Artificial intelligence, Natural language processing, Embedding, Frame and Dynamic time warping. His work in the fields of Artificial intelligence, such as Knowledge extraction, intersects with other areas such as Reading comprehension. His studies in Natural language processing integrate themes in fields like Matching, Artificial neural network, Task analysis and Turkish.

The concepts of his Embedding study are interwoven with issues in Sentence, Encoder, Graph and Spoken language. Frame overlaps with fields such as Vocabulary, Context model, Recurrent neural network, TIMIT and Task in his research. The Dynamic time warping study combines topics in areas such as Acoustic model and Phone.

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

Lattice-Based Search for Spoken Utterance Retrieval

Murat Saraclar;Richard Sproat.
north american chapter of the association for computational linguistics (2004)

337 Citations

Discriminative n-gram language modeling

Brian Roark;Murat Saraclar;Michael Collins.
Computer Speech & Language (2007)

227 Citations

Stochastic pronunciation modelling from hand-labelled phonetic corpora

Michael Riley;William Byrne;Michael Finke;Sanjeev Khudanpur.
Speech Communication (1999)

209 Citations

System and Method of Lattice-Based Search for Spoken Utterance Retrieval

Murat Saraclar;Richard William Sproat.
(2005)

207 Citations

Retrieval and browsing of spoken content

C. Chelba;T.J. Hazen;M. Saraclar.
IEEE Signal Processing Magazine (2008)

202 Citations

Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm

Brian Roark;Murat Saraclar;Michael Collins;Mark Johnson.
meeting of the association for computational linguistics (2004)

197 Citations

Morph-based speech recognition and modeling of out-of-vocabulary words across languages

Mathias Creutz;Teemu Hirsimäki;Mikko Kurimo;Antti Puurula.
ACM Transactions on Speech and Language Processing (2007)

180 Citations

Turkish Language Resources: Morphological Parser, Morphological Disambiguator and Web Corpus

Haşim Sak;Tunga Güngör;Murat Saraçlar.
international conference natural language processing (2008)

177 Citations

Lattice Indexing for Spoken Term Detection

D. Can;M. Saraclar.
IEEE Transactions on Audio, Speech, and Language Processing (2011)

175 Citations

Pronunciation modeling by sharing Gaussian densities across phonetic models

Murat Saraçlar;Harriet Nock;Sanjeev Khudanpur.
Computer Speech & Language (2000)

158 Citations

Best Scientists Citing Murat Saraclar

Lin-Shan Lee

Lin-Shan Lee

National Taiwan University

Publications: 36

Hermann Ney

Hermann Ney

RWTH Aachen University

Publications: 23

Thomas R. Gruber

Thomas R. Gruber

Apple (United States)

Publications: 22

Sanjeev Khudanpur

Sanjeev Khudanpur

Johns Hopkins University

Publications: 21

Bhuvana Ramabhadran

Bhuvana Ramabhadran

Google (United States)

Publications: 21

Haizhou Li

Haizhou Li

Chinese University of Hong Kong, Shenzhen

Publications: 21

Jerome R. Bellegarda

Jerome R. Bellegarda

Apple (United States)

Publications: 20

Brian Kingsbury

Brian Kingsbury

IBM (United States)

Publications: 17

William Byrne

William Byrne

University of Cambridge

Publications: 17

Hsin-Min Wang

Hsin-Min Wang

Academia Sinica

Publications: 17

Mari Ostendorf

Mari Ostendorf

University of Washington

Publications: 17

Pascale Fung

Pascale Fung

Hong Kong University of Science and Technology

Publications: 16

Eng Siong Chng

Eng Siong Chng

Nanyang Technological University

Publications: 15

Shinji Watanabe

Shinji Watanabe

Carnegie Mellon University

Publications: 15

Dong Wang

Dong Wang

Dalian University of Technology

Publications: 15

Ciprian Chelba

Ciprian Chelba

Google (United States)

Publications: 15

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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