Alan McCree

3.5k citations

84 papers · 2.1k indexed · h-index 23

Impact in

Signal Processing top 0.2%
- Speech and Audio Processing
- Music and Audio Processing
- Digital Filter Design and Implementation
Artificial Intelligence top 0.5%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling

Papers in ⓘ

Signal Processing 64
- Speech and Audio Processing 61
- Music and Audio Processing 35
- Digital Filter Design and Implementation 4
Artificial Intelligence 60
- Speech Recognition and Synthesis 58
- Natural Language Processing Techniques 10

Co-authors: Daniel Garcia-Romero (32 shared papers)T.P. Barnwell (7 shared papers)Gregory Sell (17 shared papers)David Snyder (10 shared papers)Daniel Povey (8 shared papers)Sanjeev Khudanpur (6 shared papers)Pedro A. Torres‐Carrasquillo (8 shared papers)V. Viswanathan (8 shared papers)
Journals: Computer Speech & Language (1 paper)IEEE Transactions on Speech and Audio Processing (1 paper)INFM-OAR (INFN Catania) (1 paper)Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing (1 paper)IEEE International Conference on Acoustics Speech and Signal Processing (2 papers)
Partner nations: United States Germany Finland

In The Last Decade

Alan McCree

79 papers receiving 1.9k citations

Peers

Countries citing papers authored by Alan McCree

Since Specialization

Citations

This map shows the geographic impact of Alan McCree's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alan McCree with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alan McCree more than expected).

Fields of papers citing papers by Alan McCree

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alan McCree. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alan McCree. The network helps show where Alan McCree may publish in the future.

Co-authors

The 25 scholars most cited alongside Alan McCree, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alan McCree Line = papers co-authored together Alan McCree links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	A mixed excitation LPC vocoder model for low bit rate speech coding IEEE Transactions on Speech and Audio Processing ·Alan McCree, T.P. Barnwell	1995	191
2	Speaker Recognition for Multi-speaker Conversations Using X-vectors David Snyder, Daniel Garcia-Romero, Gregory Sell, Alan McCree, Daniel Povey, Sanjeev Khudanpur	2019	180
3	Spoken Language Recognition using X-vectors David Snyder, Daniel Garcia-Romero, Alan McCree, Gregory Sell, Daniel Povey, Sanjeev Khudanpur	2018	121
4	MELP: the new Federal Standard at 2400 bps L.M. Supplee, R.P. Cohn, John Collura, Alan McCree	2002	118
5	Speaker diarization using deep neural network embeddings Daniel Garcia-Romero, David Snyder, Gregory Sell, Daniel Povey, Alan McCree	2017	116
6	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, Jesús Villalba, Matthew Maciejewski, Vimal Manohar, Najim Dehak, Daniel Povey, Shinji Watanabe, Sanjeev Khudanpur	2018	115
7	Supervised domain adaptation for I-vector based speaker recognition Daniel Garcia-Romero, Alan McCree	2014	89
8	Unsupervised Domain Adaptation for I-Vector Speaker Recognition Niko Brümmer, Alan McCree, Stephen Shum, Daniel Garcia-Romero, Carlos Vaquero	2014	79
9	State-of-the-art speaker recognition with neural network embeddings in NIST SRE18 and Speakers in the Wild evaluations Computer Speech & Language ·Jesús Villalba, Nanxin Chen, David Snyder, Daniel Garcia-Romero, Alan McCree, Gregory Sell, Jonas Borgstrom, Leibny Paola Garcia, Fred Richardson, Réda Dehak, Pedro A. Torres‐Carrasquillo, Najim Dehak	2019	78
10	A 2.4 kbit/s MELP coder candidate for the new U.S. Federal Standard Alan McCree, Kwan Truong, E.B. George, T.P. Barnwell, V. Viswanathan	2002	69
11	The NIST 2014 Speaker Recognition i-vector Machine Learning Challenge Alan McCree, Douglas A. Reynolds, Daniel Garcia-Romero, Tomi Kinnunen, Craig S. Greenberg, Désiré Bansé, George R. Doddington, John J. Godfrey, Alvin F. Martín, Mark A. Przybocki	2014	54
12	Improving speaker recognition performance in the domain adaptation challenge using deep neural networks Daniel Garcia-Romero, Xiaohui Zhang, Alan McCree, Daniel Povey	2014	53
13	Automatic detection of depression in speech using Gaussian mixture modeling with factor analysis Douglas Sturim, Pedro A. Torres‐Carrasquillo, Thomas F. Quatieri, Nicolas Malyska, Alan McCree	2011	51
14	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, Alan McCree, Gregory Sell, Jonas Borgstrom, Fred Richardson, Suwon Shon, François Grondin, Réda Dehak, Leibny Paola Garcia, Daniel Povey, Pedro A. Torres‐Carrasquillo, Sanjeev Khudanpur, Najim Dehak	2019	50
15	Unsupervised Clustering Approaches for Domain Adaptation in Speaker Recognition Systems Alan McCree, Stephen Shum, Douglas R. Reynolds, Daniel Garcia-Romero	2014	41
16	The MITLL NIST LRE 2009 language recognition system Pedro A. Torres‐Carrasquillo, Elliot Singer, Terry Gleason, Alan McCree, Douglas A. Reynolds, Fred Richardson, Douglas Sturim	2010	39
17	The MITLL NIST LRE 2007 language recognition system Pedro A. Torres‐Carrasquillo, Elliot Singer, William M. Campbell, Terry Gleason, Alan McCree, Douglas A. Reynolds, Fred Richardson, Wade Shen, Douglas Sturim	2008	34
18	Insights into deep neural networks for speaker recognition Daniel Garcia-Romero, Alan McCree	2015	33
19	The MITLL NIST LRE 2011 language recognition system. Elliot Singer, Pedro A. Torres‐Carrasquillo, Douglas A. Reynolds, Alan McCree, Fred Richardson, Najim Dehak, Douglas Sturim	2012	32
20	New methods for adaptive noise suppression Levent M. Arslan, Alan McCree, V. Viswanathan	2002	32

About Alan McCree

Alan McCree is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics and Computer Networks and Communications, having authored 84 papers that have together received 2.1k indexed citations. Recurring topics across this work include Speech and Audio Processing (61 papers), Speech Recognition and Synthesis (58 papers), Music and Audio Processing (35 papers), Advanced Data Compression Techniques (31 papers), Natural Language Processing Techniques (10 papers), Advanced Adaptive Filtering Techniques (8 papers), Advanced Wireless Communication Techniques (4 papers) and Digital Filter Design and Implementation (4 papers). The work is most often cited by research in Signal Processing (1.7k citations), Artificial Intelligence (1.6k citations), Computer Vision and Pattern Recognition (507 citations), Experimental and Cognitive Psychology (96 citations) and Computational Mechanics (138 citations). Alan McCree has collaborated with scholars based in United States, Germany and Finland. Frequent co-authors include Daniel Garcia-Romero, T.P. Barnwell, Gregory Sell, David Snyder, Daniel Povey, Sanjeev Khudanpur, Pedro A. Torres‐Carrasquillo, V. Viswanathan, Douglas Sturim and John Collura. Their work appears in journals such as Computer Speech & Language, IEEE Transactions on Speech and Audio Processing, INFM-OAR (INFN Catania), Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing and IEEE International Conference on Acoustics Speech and Signal Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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