H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 30 Citations 4,915 253 World Ranking 8307 National Ranking 487

Research.com Recognitions

Awards & Achievements

2020 - IEEE Fellow For contributions to signal processing for speech dereverberation and analysis

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Algorithm

Patrick A. Naylor mostly deals with Algorithm, Reverberation, Speech recognition, Speech processing and Acoustics. His study looks at the relationship between Algorithm and fields such as Noise reduction, as well as how they intersect with chemical problems. His work deals with themes such as Acoustic source localization, Noise measurement, Microphone and Impulse response, which intersect with Reverberation.

The Voice activity detection research Patrick A. Naylor does as part of his general Speech recognition study is frequently linked to other disciplines of science, such as Electroglottograph, therefore creating a link between diverse domains of science. His Speech processing research is multidisciplinary, relying on both Intelligibility, Speech coding, Speech synthesis and Linear prediction. His research in the fields of Architectural acoustics overlaps with other disciplines such as Spherical harmonics.

His most cited work include:

  • Estimation of Glottal Closure Instants in Voiced Speech Using the DYPSA Algorithm (257 citations)
  • Speech Dereverberation (240 citations)
  • Detection of Glottal Closure Instants From Speech Signals: A Quantitative Review (184 citations)

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

Speech recognition, Algorithm, Reverberation, Acoustics and Speech processing are his primary areas of study. His Speech recognition research includes elements of Speech enhancement, Noise, Pattern recognition and Artificial intelligence. His Speech enhancement research integrates issues from Noise measurement and Noise reduction.

When carried out as part of a general Algorithm research project, his work on Adaptive filter is frequently linked to work in Impulse, therefore connecting diverse disciplines of study. His study looks at the relationship between Reverberation and topics such as Microphone, which overlap with Linear prediction and Direction of arrival. His Acoustics study integrates concerns from other disciplines, such as Microphone array, Beamforming and Signal processing.

He most often published in these fields:

  • Speech recognition (47.40%)
  • Algorithm (32.33%)
  • Reverberation (26.03%)

What were the highlights of his more recent work (between 2016-2021)?

  • Speech recognition (47.40%)
  • Artificial intelligence (14.79%)
  • Reverberation (26.03%)

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

Patrick A. Naylor focuses on Speech recognition, Artificial intelligence, Reverberation, Microphone and Algorithm. Patrick A. Naylor has included themes like Kalman filter and Speech enhancement in his Speech recognition study. His Artificial intelligence study combines topics in areas such as Computer vision and Pattern recognition.

His studies deal with areas such as Noise, Noise and Robustness as well as Reverberation. His research on Microphone also deals with topics like

  • Acoustics which connect with Impulse response,
  • Tracking which connect with Real-time computing. His Algorithm research incorporates themes from Direction of arrival, Parametric model and Eigendecomposition of a matrix.

Between 2016 and 2021, his most popular works were:

  • The LOCATA Challenge Data Corpus for Acoustic Source Localization and Tracking (42 citations)
  • Acoustic SLAM (34 citations)
  • Direction of Arrival Estimation in the Spherical Harmonic Domain Using Subspace Pseudointensity Vectors (34 citations)

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

  • Artificial intelligence
  • Statistics
  • Algorithm

His primary areas of investigation include Speech recognition, Reverberation, Microphone, Artificial intelligence and Microphone array. Within one scientific family, he focuses on topics pertaining to Speech enhancement under Speech recognition, and may sometimes address concerns connected to Noise reduction and Noise measurement. His biological study spans a wide range of topics, including Acoustic source localization, Direction of arrival, Tracking, Noise and Algorithm.

His studies in Microphone integrate themes in fields like Robustness and Audio signal. His research integrates issues of Computer vision and Pattern recognition in his study of Artificial intelligence. The various areas that Patrick A. Naylor examines in his Microphone array study include Loudspeaker and Signal processing.

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

Speech Dereverberation

Patrick A. Naylor;Nikolay D. Gaubitch.
(2010)

581 Citations

Estimation of Glottal Closure Instants in Voiced Speech Using the DYPSA Algorithm

P.A. Naylor;A. Kounoudes;J. Gudnason;M. Brookes.
IEEE Transactions on Audio, Speech, and Language Processing (2007)

337 Citations

Detection of Glottal Closure Instants From Speech Signals: A Quantitative Review

T. Drugman;M. Thomas;J. Gudnason;P. Naylor.
IEEE Transactions on Audio, Speech, and Language Processing (2012)

229 Citations

EVALUATION OF SPEECH DEREVERBERATION ALGORITHMS USING THE MARDY DATABASE

Nikolay D. Gaubitch;Tony Myatt;Patrick A. Naylor.
(2006)

157 Citations

Estimation of Glottal Closing and Opening Instants in Voiced Speech Using the YAGA Algorithm

M. R. P. Thomas;J. Gudnason;P. A. Naylor.
IEEE Transactions on Audio, Speech, and Language Processing (2012)

125 Citations

Inference of Room Geometry From Acoustic Impulse Responses

F. Antonacci;J. Filos;M. R. P. Thomas;E. A. P. Habets.
IEEE Transactions on Audio, Speech, and Language Processing (2012)

120 Citations

Blind estimation of reverberation time based on the distribution of signal decay rates

J.Y.C. Wen;E.A.P. Habets;P.A. Naylor.
international conference on acoustics, speech, and signal processing (2008)

110 Citations

Adaptive algorithms for sparse echo cancellation

Patrick A. Naylor;Jingjing Cui;Mike Brookes.
Signal Processing (2006)

109 Citations

The DYPSA algorithm for estimation of glottal closure instants in voiced speech

Anastasis Kounoudes;Patrick A. Naylor;Mike Brookes.
international conference on acoustics, speech, and signal processing (2002)

97 Citations

Theory and Applications of Spherical Microphone Array Processing

Daniel P. Jarrett;Emanuël A.P. Habets;Patrick A. Naylor.
(2016)

97 Citations

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