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Computer Science

D-Index
46
Citations
58433
World Ranking
6627
National Ranking
2924

Overview

Abdel-rahman Mohamed is affiliated with Facebook in the United States. Their research primarily focuses on computer science, with a specialization in artificial intelligence, signal processing, cognitive neuroscience, and experimental and cognitive psychology.

The scientist's work covers multiple topics including speech recognition and synthesis, music and audio processing, topic modeling, speech and audio processing, natural language processing techniques, hearing loss and rehabilitation, and neuroscience and music perception.

Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • 2022 IEEE Spoken Language Technology Workshop (SLT)
  • IEEE Signal Processing Magazine
  • ConductScience Proceedings

Recent papers authored by Abdel-rahman Mohamed involve research on speech representation learning, neural computations in auditory pathways, and language modeling in dialogue systems. Notable papers include:

  • "wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations," 2020, arXiv (Cornell University)
  • "HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units," 2021, IEEE/ACM Transactions on Audio Speech and Language Processing
  • "Dissecting neural computations in the human auditory pathway using deep neural networks for speech," 2023, Nature Neuroscience
  • "SUPERB: Speech processing Universal PERformance Benchmark," 2021, arXiv (Cornell University)
  • "Generative Spoken Dialogue Language Modeling," 2023, Transactions of the Association for Computational Linguistics

Abdel-rahman Mohamed has collaborated frequently with several researchers, including:

  • Shang-Wen Li
  • Shinji Watanabe
  • Hung-yi Lee
  • Wei-Ning Hsu
  • Kushal Lakhotia

The body of work spans over 44 publications in computer science-related fields, with 30 publications focusing on artificial intelligence and 14 in signal processing. The research reflects broad interdisciplinary engagement, contributing to improved understanding and technologies in speech and audio domains alongside cognitive neuroscience aspects.

Best Publications

  • Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

    G. Hinton;Li Deng;Dong Yu;G. E. Dahl

  • Speech recognition with deep recurrent neural networks

    Alex Graves;Abdel-rahman Mohamed;Geoffrey Hinton

  • BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

    Mike Lewis;Yinhan Liu;Naman Goyal;Marjan Ghazvininejad

  • Deep Neural Networks for Acoustic Modeling in Speech Recognition

    Geoffrey Hinton;Li Deng;Dong Yu;George Dahl

  • Convolutional neural networks for speech recognition

    Ossama Abdel-Hamid;Abdel-Rahman Mohamed;Hui Jiang;Li Deng

  • wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

    Alexei Baevski;Henry Zhou;Abdelrahman Mohamed;Michael Auli

  • Acoustic Modeling Using Deep Belief Networks

    A. Mohamed;G. E. Dahl;G. Hinton

  • Hybrid speech recognition with Deep Bidirectional LSTM

    Alex Graves;Navdeep Jaitly;Abdel-rahman Mohamed

  • Deep Convolutional Neural Networks for Large-scale Speech Tasks

    Tara N. Sainath;Brian Kingsbury;George Saon;Hagen Soltau

  • HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units

    Wei-Ning Hsu;Benjamin Bolte;Yao-Hung Hubert Tsai;Kushal Lakhotia

  • Deep convolutional neural networks for LVCSR

    Tara N. Sainath;Abdel-rahman Mohamed;Brian Kingsbury;Bhuvana Ramabhadran

  • Applying Convolutional Neural Networks concepts to hybrid NN-HMM model for speech recognition

    Ossama Abdel-Hamid;Abdel-rahman Mohamed;Hui Jiang;Gerald Penn

  • wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

    Alexei Baevski;Yuhao Zhou;Abdelrahman Mohamed;Michael Auli

  • SUPERB: Speech processing Universal PERformance Benchmark

    Shu-wen Yang;Po-Han Chi;Yung-Sung Chuang;Cheng-I Jeff Lai

  • Unsupervised Cross-lingual Representation Learning for Speech Recognition

    Alexis Conneau;Alexei Baevski;Ronan Collobert;Abdelrahman Mohamed

  • Binary Coding of Speech Spectrograms Using a Deep Auto-encoder

    Li Deng;Michael L. Seltzer;Dong Yu;Alex Acero

  • Self-Supervised Speech Representation Learning: A Review

    Unknown

  • Libri-Light: A Benchmark for ASR with Limited or No Supervision

    J. Kahn;M. Riviere;W. Zheng;E. Kharitonov

  • Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine

    George Dahl;Marc'aurelio Ranzato;Abdel-rahman Mohamed;Geoffrey E. Hinton

  • Deep Belief Networks using discriminative features for phone recognition

    Abdel-rahman Mohamed;Tara N. Sainath;George Dahl;Bhuvana Ramabhadran

  • The shared views of four research groups )

    Geoffrey Hinton;Li Deng;Dong Yu;George E. Dahl

Frequent Co-Authors

Tara N. Sainath
Tara N. Sainath Google (United States)
Brian Kingsbury
Brian Kingsbury IBM (United States)
Geoffrey E. Hinton
Geoffrey E. Hinton University of Toronto
Bhuvana Ramabhadran
Bhuvana Ramabhadran Google (United States)
Pushmeet Kohli
Pushmeet Kohli DeepMind (United Kingdom)
George E. Dahl
George E. Dahl Google (United States)
Li Deng
Li Deng Citadel
Rich Caruana
Rich Caruana Microsoft (United States)
Matthew Richardson
Matthew Richardson Microsoft (United States)
Dong Yu
Dong Yu Tencent (China)

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