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D-Index & Metrics

Computer Science

D-Index
53
Citations
10298
World Ranking
4864
National Ranking
2266

Overview

Richard M. Stern is affiliated with Carnegie Mellon University in the United States. Their research spans primarily the field of Computer Science, with a significant focus on signal processing and artificial intelligence. Additional subfields include geophysics, electrical and electronic engineering, and computational mechanics.

The main topics of their work cover speech and audio processing, speech recognition and synthesis, and music and audio processing. Their research also involves advanced adaptive filtering techniques, indoor and outdoor localization technologies, hearing loss and rehabilitation, and the study of random lasers and scattering media.

Richard M. Stern has contributed to several recent publications, including:

  • "Speedy light focusing through scattering media by a cooperatively FPGA-parameterized genetic algorithm" (2022), published in Optics Express
  • "A unified beamforming and source separation model for static and dynamic human-robot interaction" (2024), published in JASA Express Letters
  • "Improved Modulation-Domain Loss for Neural-Network-based Speech Enhancement" (2022), published in Interspeech 2022
  • "Discovery of a giant juvenile 3.3-3.1 Ga terrane in the Rae craton, Canada" (2022), published in Goldschmidt2022 abstracts
  • "Non causal deep learning based dereverberation" (2020), published in arXiv (Cornell University)

The frequent publication venues include:

  • arXiv (Cornell University)
  • Goldschmidt2022 abstracts
  • Sensors
  • Geostandards and Geoanalytical Research
  • Optics Express

Collaborations form an important aspect of their research. Frequent coauthors are:

  • Néstor Becerra Yoma
  • Jorge Wuth
  • Rodrigo Mahú
  • Tyler Vuong
  • Alejandro Luzanto

Best Publications

  • An approach to cardiac arrhythmia analysis using hidden Markov models

    D.A. Coast;R.M. Stern;G.G. Cano;S.A. Briller

  • A vector Taylor series approach for environment-independent speech recognition

    P.J. Moreno;B. Raj;R.M. Stern

  • Power-normalized cepstral coefficients (PNCC) for robust speech recognition

    Chanwoo Kim;Richard M. Stern

  • Environmental robustness in automatic speech recognition

    A. Acero;R.M. Stern

  • Reconstruction of missing features for robust speech recognition

    Bhiksha Raj;Michael L. Seltzer;Richard M. Stern

  • Missing-feature approaches in speech recognition

    B. Raj;R.M. Stern

  • Multiple approaches to robust speech recognition.

    Richard M. Stern;Fu-Hua Liu;Yoshiaki Ohshima;Thomas M. Sullivan

  • Power-Normalized Cepstral Coefficients (PNCC) for robust speech recognition

    Chanwoo Kim;Richard M. Stern

  • Theory of binaural interaction based on auditory‐nerve data. IV. A model for subjective lateral position

    Richard M. Stern;H. Steven Colburn

  • Lateralization of complex binaural stimuli: A weighted‐image model

    Richard M. Stern;Andrew S. Zeiberg;Constantine Trahiotis

  • Efficient cepstral normalization for robust speech recognition

    Fu-Hua Liu;Richard M. Stern;Xuedong Huang;Alejandro Acero

  • A Bayesian Classifier for Spectrographic Mask Estimation for Missing Feature Speech Recognition

    Michael L. Seltzer;Bhiksha Raj;Richard M. Stern

  • Robust speech recognition by normalization of the acoustic space

    A. Acero;R.M. Stern

  • Robust signal-to-noise ratio estimation based on waveform amplitude distribution analysis.

    Chanwoo Kim;Richard M. Stern

  • Efficient joint compensation of speech for the effects of additive noise and linear filtering

    F.-H. Liu;A. Acero;R.M. Stern

  • Fast Computation of the Difference of Low-Pass Transform

    James L. Crowley;Richard M. Stern

  • Likelihood-maximizing beamforming for robust hands-free speech recognition

    M.L. Seltzer;B. Raj;R.M. Stern

  • On the effects of speech rate in large vocabulary speech recognition systems

    M.A. Siegler;R.M. Stern

  • Feature extraction for robust speech recognition based on maximizing the sharpness of the power distribution and on power flooring

    Chanwoo Kim;Richard M. Stern

  • Delta-spectral cepstral coefficients for robust speech recognition

    Kshitiz Kumar;Chanwoo Kim;Richard M. Stern

Frequent Co-Authors

Bhiksha Raj
Bhiksha Raj Carnegie Mellon University
Pedro J. Moreno
Pedro J. Moreno Google (United States)
Michael L. Seltzer
Michael L. Seltzer Facebook (United States)
Alejandro Acero
Alejandro Acero Apple (United States)
Alexander G. Hauptmann
Alexander G. Hauptmann Carnegie Mellon University
Florian Metze
Florian Metze Carnegie Mellon University
Teruko Mitamura
Teruko Mitamura Carnegie Mellon University
Constantine Trahiotis
Constantine Trahiotis University of Connecticut Health Center
Eric Nyberg
Eric Nyberg Carnegie Mellon University
H. Steven Colburn
H. Steven Colburn Boston University

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