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Computer Science

D-Index
47
Citations
9232
World Ranking
6472
National Ranking
2874

Research.com Recognitions

  • 2018 - IEEE Fellow For contributions to automatic speech recognition using Weighted Finite-State Transducers

Overview

Michael Riley is a researcher affiliated with Google in the United States.

Their research primarily spans the fields of Computer Science and Engineering, with a focus on several subfields including Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering, Computer Networks and Communications, and Human-Computer Interaction.

The main topics covered in their work include:

  • Millimeter-Wave Propagation and Modeling
  • Advanced MIMO Systems Optimization
  • Wireless Body Area Networks
  • Natural Language Processing Techniques
  • Wireless Signal Modulation Classification
  • Distributed Sensor Networks and Detection Algorithms
  • Target Tracking and Data Fusion in Sensor Networks

Michael Riley's recent papers reflect collaboration and contributions in various aspects of communications, privacy, and language processing. Notable publications include:

  • "Self-Supervised Adaptive Weighting for Cooperative Perception in V2V Communications" (2023) published in IEEE Transactions on Intelligent Vehicles
  • "Cooperative Perception With Learning-Based V2V Communications" (2023) published in IEEE Wireless Communications Letters
  • "Learning discrete distributions: user vs item-level privacy" (2020) published on arXiv (Cornell University)
  • "Spatial Model Personalization in Gboard" (2022) published in Proceedings of the ACM on Human-Computer Interaction
  • "Approximating Probabilistic Models as Weighted Finite Automata" (2021) published in Computational Linguistics

Their frequent coauthors include Chenguang Liu, Jianjun Chen, Yunfei Chen, Ryan L. Payton, and Shuang-Hua Yang, each collaborating on multiple works.

Michael Riley has published in a range of venues where they have multiple contributions, particularly arXiv (Cornell University) with three papers, as well as single publications in IEEE Transactions on Intelligent Vehicles, IEEE Wireless Communications Letters, Proceedings of the ACM on Human-Computer Interaction, and Computational Linguistics.

In 2018, Michael Riley was recognized as an IEEE Fellow for contributions to automatic speech recognition using Weighted Finite-State Transducers.

Best Publications

  • Weighted finite-state transducers in speech recognition

    Mehryar Mohri;Fernando Pereira;Michael Riley

  • OpenFst: a general and efficient weighted finite-state transducer library

    Cyril Allauzen;Michael Riley;Johan Schalkwyk;Wojciech Skut

  • Speech Recognition with Weighted Finite-State Transducers

    Mehryar Mohri;Fernando C. N. Pereira;Michael Riley

  • Sample Selection Bias Correction Theory

    Corinna Cortes;Mehryar Mohri;Michael Riley;Afshin Rostamizadeh

  • Methods and Apparatus for Rapid Acoustic Unit Selection From a Large Speech Corpus

    Mark Charles Beutnagel;Mehryar Mohri;Michael Dennis Riley

  • Tree-Based Modelling of Segmental Duration

    M. Riley

  • A design principles of a weighted finite-state transducer library

    Mehryar Mohri;Fernando Pereira;Michael Riley

  • Stochastic pronunciation modelling from hand-labelled phonetic corpora

    Michael Riley;William Byrne;Michael Finke;Sanjeev Khudanpur

  • The hub and spoke paradigm for CSR evaluation

    Francis Kubala;Jerome Bellegarda;Jordan Cohen;David Pallett

  • Some applications of tree-based modelling to speech and language

    Michael D. Riley

  • A Rational Design for a Weighted Finite-State Transducer Library

    Mehryar Mohri;Fernando C. N. Pereira;Michael Riley

  • Speech Recognition by Composition of Weighted Finite Automata

    Fernando C. N. Pereira;Michael Riley

  • Weighted Automata in Text and Speech Processing

    Mehryar Mohri;Fernando Pereira;Michael Riley

  • Fully expanded context-dependent networks for speech recognition

    Mehryar Mohri;Michael Dennis Riley

  • Systems and methods for determinizing and minimizing a finite state transducer for speech recognition

    Mehryar Mohri;Fernando Carlos Neves Pereira;Michael Dennis Riley

  • Voice signatures

    I. Shafran;M. Riley;M. Mohri

  • Keyboard for interacting on small devices

    Nils Klarlund;Michael Dennis Riley

  • Compilation of Weighted Finite-State Transducers from Decision Trees

    Richard Sproat;Michael Riley

  • Automatic segmentation and labeling of speech

    A. Ljolje;M.D. Riley

  • Weighted rational transductions and their application to human language processing

    Fernando Pereira;Michael Riley;Richard Sproat

  • Hybrid Autoregressive Transducer (HAT)

    Ehsan Variani;David Rybach;Cyril Allauzen;Michael Riley

Frequent Co-Authors

Mehryar Mohri
Mehryar Mohri Google (United States)
Fernando Pereira
Fernando Pereira Google (United States)
Richard Sproat
Richard Sproat Google (United States)
Brian Roark
Brian Roark Google (United States)
Murat Saraclar
Murat Saraclar Boğaziçi University
Corinna Cortes
Corinna Cortes Google (United States)
Sanjeev Khudanpur
Sanjeev Khudanpur Johns Hopkins University
Chuck Wooters
Chuck Wooters International Computer Science Institute
Francoise Beaufays
Francoise Beaufays Google (United States)
Ciprian Chelba
Ciprian Chelba Google (United States)

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