World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
8084
World Ranking
7577
National Ranking
3288

Overview

Jasha Droppo is affiliated with Amazon (United States) and has a research profile focused primarily within the field of Computer Science. Their work spans subfields including Artificial Intelligence, Signal Processing, Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition, and Clinical Psychology.

Their research topics predominantly cover Speech Recognition and Synthesis, Speech and Audio Processing, Music and Audio Processing, Natural Language Processing Techniques, Topic Modeling, Phonetics and Phonology Research, and Domain Adaptation and Few-Shot Learning.

Jasha Droppo has contributed to several papers published in notable venues. These include:

  • "Improving Fairness in Speaker Verification via Group-Adapted Fusion Network," 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • "ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale," 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • "Improved Representation Learning For Acoustic Event Classification Using Tree-Structured Ontology," 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • "Adversarial Reweighting for Speaker Verification Fairness," 2022, Interspeech 2022
  • "Reducing Geographic Disparities in Automatic Speech Recognition via Elastic Weight Consolidation," 2022, Interspeech 2022

The frequent co-authors collaborating with Jasha Droppo include:

  • Andreas Stolcke
  • Brian King
  • Ariya Rastrow
  • Roland Maas
  • Gautam Tiwari

In terms of publication venues, Jasha Droppo often publishes in:

  • arXiv (Cornell University)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Interspeech 2022
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • 2022 IEEE Spoken Language Technology Workshop (SLT)

Best Publications

  • 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs.

    Frank Seide;Hao Fu;Jasha Droppo;Gang Li

  • The Microsoft 2017 Conversational Speech Recognition System

    W. Xiong;L. Wu;F. Alleva;J. Droppo

  • Achieving Human Parity in Conversational Speech Recognition

    Wayne Xiong;Jasha Droppo;Xuedong Huang;Frank Seide

  • An Introduction to Computational Networks and the Computational Network Toolkit

    Dong Yu;Adam Eversole;Mike Seltzer;Kaisheng Yao

  • Multi-task learning in deep neural networks for improved phoneme recognition

    Michael L. Seltzer;Jasha Droppo

  • The microsoft 2016 conversational speech recognition system

    W. Xiong;J. Droppo;X. Huang;F. Seide

  • Toward Human Parity in Conversational Speech Recognition

    Wayne Xiong;Jasha Droppo;Xuedong Huang;Frank Seide

  • Dynamic compensation of HMM variances using the feature enhancement uncertainty computed from a parametric model of speech distortion

    Li Deng;J. Droppo;A. Acero

  • Uncertainty decoding with SPLICE for noise robust speech recognition

    Jasha Droppo;Alex Acero;Li Deng

  • High-performance robust speech recognition using stereo training data

    Li Deng;A. Acero;Li Jiang;J. Droppo

  • Evaluation of the SPLICE algorithm on the Aurora2 database.

    Jasha Droppo;Li Deng;Alex Acero

  • Enhancement of log Mel power spectra of speech using a phase-sensitive model of the acoustic environment and sequential estimation of the corrupting noise

    Li Deng;J. Droppo;A. Acero

  • Recursive estimation of nonstationary noise using iterative stochastic approximation for robust speech recognition

    Li Deng;J. Droppo;A. Acero

  • On parallelizability of stochastic gradient descent for speech DNNS

    Frank Seide;Hao Fu;Jasha Droppo;Gang Li

  • A minimum-mean-square-error noise reduction algorithm on Mel-frequency cepstra for robust speech recognition

    Dong Yu;Li Deng;J. Droppo;Jian Wu

  • Improving speech recognition in reverberation using a room-aware deep neural network and multi-task learning

    Ritwik Giri;Michael L. Seltzer;Jasha Droppo;Dong Yu

  • Air- and bone-conductive integrated microphones for robust speech detection and enhancement

    Yanli Zheng;Zicheng Liu;Zhengyou Zhang;M. Sinclair

  • Advances in all-neural speech recognition

    Geoffrey Zweig;Chengzhu Yu;Jasha Droppo;Andreas Stolcke

  • Deep neural networks for single-channel multi-talker speech recognition

    Chao Weng;Dong Yu;Michael L. Seltzer;Jasha Droppo

  • Deep Convolutional Neural Networks with Layer-Wise Context Expansion and Attention.

    Dong Yu;Wayne Xiong;Jasha Droppo;Andreas Stolcke

  • Noise Adaptive Training for Robust Automatic Speech Recognition

    O Kalinli;M L Seltzer;J Droppo;A Acero

Frequent Co-Authors

Li Deng
Li Deng Citadel
Alejandro Acero
Alejandro Acero Apple (United States)
Michael L. Seltzer
Michael L. Seltzer Facebook (United States)
Dong Yu
Dong Yu Tencent (China)
Xuedong Huang
Xuedong Huang Microsoft (United States)
Frank Seide
Frank Seide Microsoft (United States)
Yifan Gong
Yifan Gong Microsoft (United States)
Les Atlas
Les Atlas University of Washington
Geoffrey Zweig
Geoffrey Zweig Facebook (United States)

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