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Computer Science

D-Index
65
Citations
39939
World Ranking
2385
National Ranking
1189

Overview

Sanjeev Khudanpur is a researcher affiliated with Johns Hopkins University in the United States. Their academic contributions are primarily situated within the field of Computer Science, with a special focus on subfields such as Artificial Intelligence, Signal Processing, and Computer Vision and Pattern Recognition.

The research portfolio of Sanjeev Khudanpur spans multiple interconnected topics. Key areas of work include:

  • Speech Recognition and Synthesis
  • Natural Language Processing Techniques
  • Speech and Audio Processing
  • Music and Audio Processing
  • Speech and dialogue systems
  • Topic Modeling
  • Multimodal Machine Learning Applications

Notable recent publications authored by or involving Sanjeev Khudanpur include:

  • "CHiME-6 Challenge: Tackling Multispeaker Speech Recognition for Unsegmented Recordings" (2020), published in arXiv (Cornell University)
  • "Investigating Self-Supervised Learning for Speech Enhancement and Separation" (2022), presented at ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • "The Hitachi-JHU DIHARD III System: Competitive End-to-End Neural Diarization and X-Vector Clustering Systems Combined by DOVER-Lap" (2021), published in arXiv (Cornell University)
  • "Efficient Self-Supervised Learning Representations for Spoken Language Identification" (2022), appearing in IEEE Journal of Selected Topics in Signal Processing
  • "GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio" (2021), available in arXiv (Cornell University)

Their frequent co-authors include:

  • Leibny Paola Garcia
  • Daniel Povey
  • Matthew Wiesner
  • Shinji Watanabe
  • Desh Raj

Sanjev Khudanpur has contributed extensively to various publication venues. The most common include:

  • arXiv (Cornell University)
  • Interspeech 2022
  • Computer Speech & Language
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2022 IEEE Spoken Language Technology Workshop (SLT)

Best Publications

  • Recurrent neural network based language model

    Tomas Mikolov;Martin Karafiát;Lukás Burget;Jan Cernocký

  • Librispeech: An ASR corpus based on public domain audio books

    Vassil Panayotov;Guoguo Chen;Daniel Povey;Sanjeev Khudanpur

  • Extensions of recurrent neural network language model

    Tomas Mikolov;Stefan Kombrink;Lukas Burget;Jan Cernocky

  • X-Vectors: Robust DNN Embeddings for Speaker Recognition

    David Snyder;Daniel Garcia-Romero;Gregory Sell;Daniel Povey

  • Audio augmentation for speech recognition.

    Tom Ko;Vijayaditya Peddinti;Daniel Povey;Sanjeev Khudanpur

  • A time delay neural network architecture for efficient modeling of long temporal contexts.

    Vijayaditya Peddinti;Daniel Povey;Sanjeev Khudanpur

  • Deep Neural Network Embeddings for Text-Independent Speaker Verification.

    David Snyder;Daniel Garcia-Romero;Daniel Povey;Sanjeev Khudanpur

  • A study on data augmentation of reverberant speech for robust speech recognition

    Tom Ko;Vijayaditya Peddinti;Daniel Povey;Michael L. Seltzer

  • Purely Sequence-Trained Neural Networks for ASR Based on Lattice-Free MMI.

    Daniel Povey;Vijayaditya Peddinti;Daniel Galvez;Pegah Ghahremani

  • Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks.

    Daniel Povey;Gaofeng Cheng;Yiming Wang;Ke Li

  • Parallel training of Deep Neural Networks with Natural Gradient and Parameter Averaging

    Daniel Povey;Xiaohui Zhang;Sanjeev Khudanpur

  • Deep neural network-based speaker embeddings for end-to-end speaker verification

    David Snyder;Pegah Ghahremani;Daniel Povey;Daniel Garcia-Romero

  • Improving deep neural network acoustic models using generalized maxout networks

    Xiaohui Zhang;Jan Trmal;Daniel Povey;Sanjeev Khudanpur

  • A pitch extraction algorithm tuned for automatic speech recognition

    Pegah Ghahremani;Bagher BabaAli;Daniel Povey;Korbinian Riedhammer

  • A Smorgasbord of Features for Statistical Machine Translation

    Franz Josef Och;Daniel Gildea;Sanjeev Khudanpur;Anoop Sarkar

  • Highway long short-term memory RNNS for distant speech recognition

    Yu Zhang;Guoguo Chen;Dong Yu;Kaisheng Yaco

  • Developments and directions in speech recognition and understanding, Part 1 [DSP Education]

    J. Baker;Li Deng;J. Glass;S. Khudanpur

  • Speaker Recognition for Multi-speaker Conversations Using X-vectors

    David Snyder;Daniel Garcia-Romero;Gregory Sell;Alan McCree

  • CHiME-6 Challenge: Tackling multispeaker speech recognition for unsegmented recordings

    Shinji Watanabe;Michael Mandel;Jon Barker;Emmanuel Vincent

  • A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery

    Narges Ahmidi;Lingling Tao;Shahin Sefati;Yixin Gao

  • GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio

    Guoguo Chen;Shuzhou Chai;Guanbo Wang;Jiayu Du

Frequent Co-Authors

Daniel Povey
Daniel Povey Xiaomi (China)
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
Murat Saraclar
Murat Saraclar Boğaziçi University
Gregory D. Hager
Gregory D. Hager Johns Hopkins University
Chris Callison-Burch
Chris Callison-Burch University of Pennsylvania
Mark Dredze
Mark Dredze Johns Hopkins University
William Byrne
William Byrne University of Cambridge
Lukas Burget
Lukas Burget Brno University of Technology
Daniel Garcia-Romero
Daniel Garcia-Romero Johns Hopkins University
Najim Dehak
Najim Dehak Johns Hopkins University

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