H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 44 Citations 7,792 119 World Ranking 3737 National Ranking 1905

Research.com Recognitions

Awards & Achievements

2002 - IEEE Fellow For development of speech recognition algorithms and products

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of investigation include Artificial intelligence, Speech recognition, Natural language processing, Pattern recognition and Vocabulary. His work carried out in the field of Artificial intelligence brings together such families of science as Context and Set. His study in Speaker recognition, Speech processing, Word error rate, Audio mining and Speech analytics falls under the purview of Speech recognition.

His study looks at the relationship between Natural language processing and topics such as User interface, which overlap with Kernel, Dialog box, Human–computer interaction and Virtual machine. He interconnects Decoding methods, Frequency band and Energy in the investigation of issues within Pattern recognition. His Vocabulary research is multidisciplinary, relying on both Word and Training set.

His most cited work include:

  • Speaker adaptation of neural network acoustic models using i-vectors (501 citations)
  • Conversational computing via conversational virtual machine (480 citations)
  • Automatic indexing and aligning of audio and text using speech recognition (370 citations)

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

David Nahamoo focuses on Artificial intelligence, Speech recognition, Pattern recognition, Vocabulary and Natural language processing. His work investigates the relationship between Artificial intelligence and topics such as Set that intersect with problems in Event. Speech recognition is closely attributed to Phone in his work.

His research integrates issues of Weighting, Feature, Feature and Speech coding in his study of Pattern recognition. His research in Vocabulary tackles topics such as Markov model which are related to areas like Pronunciation, Confusion matrix and Probability distribution. His studies in Natural language processing integrate themes in fields like Context, Dialog system, Dialog box and Utterance.

He most often published in these fields:

  • Artificial intelligence (56.29%)
  • Speech recognition (53.64%)
  • Pattern recognition (29.14%)

What were the highlights of his more recent work (between 2011-2020)?

  • Artificial intelligence (56.29%)
  • Speech recognition (53.64%)
  • Dialog box (7.28%)

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

David Nahamoo mainly investigates Artificial intelligence, Speech recognition, Dialog box, Speaker recognition and Natural language processing. His studies deal with areas such as Machine learning and Pattern recognition as well as Artificial intelligence. His research in Speech recognition intersects with topics in Sparse approximation, Feature and Representation.

His Dialog box study incorporates themes from Computer program, User interface and Information retrieval. His Speaker recognition study combines topics in areas such as Acoustic model and Session. In his study, Character, Benchmark, Word, Contrast and Hidden Markov model is inextricably linked to Phone, which falls within the broad field of Word error rate.

Between 2011 and 2020, his most popular works were:

  • Speaker adaptation of neural network acoustic models using i-vectors (501 citations)
  • Direct Acoustics-to-Word Models for English Conversational Speech Recognition (74 citations)
  • Exemplar-Based Processing for Speech Recognition: An Overview (49 citations)

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

Speaker adaptation of neural network acoustic models using i-vectors

George Saon;Hagen Soltau;David Nahamoo;Michael Picheny.
ieee automatic speech recognition and understanding workshop (2013)

611 Citations

Conversational computing via conversational virtual machine

Maes Stephane H.
(1999)

521 Citations

Automatic indexing and aligning of audio and text using speech recognition

Hamed A. Ellozy;Dimitri Kanevsky;Michelle Y. Kim;David Nahamoo.
(1995)

486 Citations

Tied mixture continuous parameter modeling for speech recognition

J.R. Bellegarda;D. Nahamoo.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1990)

297 Citations

An inequality for rational functions with applications to some statistical estimation problems

P.S. Gopalakrishnan;D. Kanevsky;A. Nadas;D. Nahamoo.
IEEE Transactions on Information Theory (1991)

281 Citations

Speech recognition using noise-adaptive prototypes

A. Nadas;D. Nahamoo;M.A. Picheny.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1989)

270 Citations

The metamorphic algorithm: a speaker mapping approach to data augmentation

J.R. Bellegarda;P.V. de Souza;A. Nadas;D. Nahamoo.
IEEE Transactions on Speech and Audio Processing (1994)

269 Citations

Multonic Markov word models for large vocabulary continuous speech recognition

L.R. Bahl;J.R. Bellegarda;P.V. de Souza;P.S. Gopalakrishnan.
IEEE Transactions on Speech and Audio Processing (1993)

256 Citations

Performance of the IBM large vocabulary continuous speech recognition system on the ARPA Wall Street Journal task

L.R. Bahl;S. Balakrishnan-Aiyer;J.R. Bellgarda;M. Franz.
international conference on acoustics, speech, and signal processing (1995)

233 Citations

Large vocabulary natural language continuous speech recognition

L.R. Bahl;R. Bakis;J. Bellegarda;P.F. Brown.
international conference on acoustics, speech, and signal processing (1989)

231 Citations

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