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Computer Science

D-Index
42
Citations
6813
World Ranking
8451
National Ranking
3613

Research.com Recognitions

  • 2005 - IEEE Fellow For contributions to low bit-rate coding of speech signals.

Overview

Alan V. McCree is affiliated with Johns Hopkins University in the United States. Their research primarily spans the fields of computer science, with particular focus on signal processing and artificial intelligence. Within these areas, they have contributed work related to speech recognition and synthesis, speech and audio processing, as well as music and audio processing.

Their recent publications include the following papers:

  • Variable frame rate-based data augmentation to handle speaking-style variability for automatic speaker verification, 2020, arXiv (Cornell University)
  • Speaker Diarization using Two-pass Leave-One-Out Gaussian PLDA Clustering of DNN Embeddings, 2021, arXiv (Cornell University)

Frequent co-authors working alongside Alan V. McCree include:

  • Amber Afshan
  • Jinxi Guo
  • Soo-Jin Park
  • Vijay Ravi
  • Abeer Alwan

Publications are predominantly found in the venue arXiv (Cornell University), where they have had multiple contributions.

The main topics of Alan V. McCree's research focus on:

  • Speech Recognition and Synthesis
  • Speech and Audio Processing
  • Music and Audio Processing

Among the distinctions received, Alan V. McCree was named an IEEE Fellow in 2005 for contributions to low bit-rate coding of speech signals.

Best Publications

  • A mixed excitation LPC vocoder model for low bit rate speech coding

    A.V. McCree;T.P. Barnwell

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

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

  • Processes, articles, and packets for network path diversity in media over packet applications

    Stephen J. Perkins;Alan Gatherer;Krishanasamy Anandakumar;Alan V. McCree

  • MELP: the new Federal Standard at 2400 bps

    L.M. Supplee;R.P. Cohn;J.S. Collura;A.V. McCree

  • Speaker diarization using deep neural network embeddings

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

  • Spoken Language Recognition using X-vectors.

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

  • Diarization is hard: Some experiences and lessons learned for the JHU team in the inaugural dihard challenge

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

  • Systems, processes and integrated circuits for rate and/or diversity adaptation for packet communications

    Krishnasamy Anandakumar;Vishu R. Viswanathan;Alan V. McCree

  • A 2.4 kbit/s MELP coder candidate for the new U.S. Federal Standard

    A. McCree;Kwan Truong;E.B. George;T.P. Barnwell

  • Wireless base station systems for packet communications

    Krishnasamy Anandakumar;Vishu R. Viswanathan;Alan V. McCree

  • Supervised domain adaptation for I-vector based speaker recognition

    Daniel Garcia-Romero;Alan McCree

  • Hybrid speech coding and system

    Jacek Stachurski;Alan V. McCree

  • Proxy pair identification communication though separate proxy devices and paths

    Stephen J. Perkins;Alan Gatherer;Krishnasamy Anandakumar;Alan V. McCree

  • UNSUPERVISED DOMAIN ADAPTATION FOR I-VECTOR SPEAKER RECOGNITION

    Niko Brummer;Alan McCree;Stephen Shum;Daniel Garcia-Romero

  • Acoustic echo devices and methods

    Alan V. McCree;Takahiro Unno;Thierry LeGall;Sebastien Guiriec

  • State-of-the-art speaker recognition with neural network embeddings in NIST SRE18 and Speakers in the Wild evaluations

    Jesús Villalba;Nanxin Chen;David Snyder;Daniel Garcia-Romero

  • The MITLL NIST LRE 2009 language recognition system

    Pedro A. Torres-Carrasquillo;Elliot Singer;Terry Gleason;Alan McCree

  • The NIST 2014 Speaker Recognition i-vector Machine Learning Challenge.

    Alan McCree;Douglas A. Reynolds;Daniel Garcia-Romero;Tomi Kinnunen

  • Adaptive weiner filtering using a dynamic suppression factor

    Levent M. Arslan;Alan V. McCree;Vishu R. Viswanathan

  • State-of-the-Art Speaker Recognition for Telephone and Video Speech: The JHU-MIT Submission for NIST SRE18.

    Jesús Villalba;Nanxin Chen;David Snyder;Daniel Garcia-Romero

  • New methods for adaptive noise suppression

    L. Arslan;A. McCree;V. Viswanathan

Frequent Co-Authors

Daniel Garcia-Romero
Daniel Garcia-Romero Johns Hopkins University
Daniel Povey
Daniel Povey Xiaomi (China)
Najim Dehak
Najim Dehak Johns Hopkins University
Sanjeev Khudanpur
Sanjeev Khudanpur Johns Hopkins University
George R. Doddington
George R. Doddington Texas Instruments (United States)
William M. Campbell
William M. Campbell Amazon (United States)
Abeer Alwan
Abeer Alwan University of California, Los Angeles
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University

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