Michael M. Goodwin

1.0k total citations
48 papers, 695 citations indexed

About

Michael M. Goodwin is a scholar working on Signal Processing, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Michael M. Goodwin has authored 48 papers receiving a total of 695 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Signal Processing, 21 papers in Computational Mechanics and 16 papers in Computer Vision and Pattern Recognition. Recurrent topics in Michael M. Goodwin's work include Speech and Audio Processing (31 papers), Advanced Adaptive Filtering Techniques (16 papers) and Music and Audio Processing (11 papers). Michael M. Goodwin is often cited by papers focused on Speech and Audio Processing (31 papers), Advanced Adaptive Filtering Techniques (16 papers) and Music and Audio Processing (11 papers). Michael M. Goodwin collaborates with scholars based in United States, Switzerland and Japan. Michael M. Goodwin's co-authors include Martin Vetterli, Jean-Marc Jot, Gary W. Elko, Edward A. Lee, J. Laroche, Juha Merimaa, Edward V. Stein, Carlos Avendaño, W. Dobrzynski and Michael Pott-Pollenske and has published in prestigious journals such as IEEE Transactions on Signal Processing, The Journal of the Acoustical Society of America and IEEE Transactions on Audio Speech and Language Processing.

In The Last Decade

Michael M. Goodwin

43 papers receiving 579 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael M. Goodwin United States 15 567 306 229 126 96 48 695
André Gilloire France 13 764 1.3× 748 2.4× 172 0.8× 86 0.7× 108 1.1× 42 851
Udo Zölzer Germany 12 309 0.5× 135 0.4× 226 1.0× 69 0.5× 81 0.8× 92 538
Jesper Kjær Nielsen Denmark 15 426 0.8× 265 0.9× 63 0.3× 134 1.1× 152 1.6× 58 631
Soo Ngee Koh Singapore 15 695 1.2× 427 1.4× 206 0.9× 101 0.8× 38 0.4× 76 881
Luiz W. P. Biscainho Brazil 12 350 0.6× 115 0.4× 143 0.6× 84 0.7× 43 0.4× 58 442
Changchun Bao China 13 657 1.2× 314 1.0× 155 0.7× 127 1.0× 51 0.5× 159 796
E. Ferrara United States 8 598 1.1× 340 1.1× 90 0.4× 116 0.9× 103 1.1× 9 782
Yoichi Haneda Japan 15 804 1.4× 478 1.6× 83 0.4× 334 2.7× 295 3.1× 109 893
K. Lebart United Kingdom 10 235 0.4× 153 0.5× 114 0.5× 79 0.6× 40 0.4× 20 465
Dae Hee Youn South Korea 14 387 0.7× 298 1.0× 189 0.8× 43 0.3× 96 1.0× 84 777

Countries citing papers authored by Michael M. Goodwin

Since Specialization
Citations

This map shows the geographic impact of Michael M. Goodwin'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 Michael M. Goodwin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael M. Goodwin more than expected).

Fields of papers citing papers by Michael M. Goodwin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael M. Goodwin. 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 Michael M. Goodwin. The network helps show where Michael M. Goodwin may publish in the future.

Co-authorship network of co-authors of Michael M. Goodwin

This figure shows the co-authorship network connecting the top 25 collaborators of Michael M. Goodwin. A scholar is included among the top collaborators of Michael M. Goodwin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael M. Goodwin. Michael M. Goodwin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Valin, Jean-Marc, et al.. (2024). NOLACE: Improving Low-Complexity Speech Codec Enhancement Through Adaptive Temporal Shaping. 476–480. 2 indexed citations
2.
Goodwin, Michael M. & Jean-Marc Jot. (2008). Spatial Audio Scene Coding. Journal of the Audio Engineering Society. 17 indexed citations
3.
Goodwin, Michael M.. (2008). Geometric signal decompositions for spatial audio enhancement. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. 54. 409–412. 16 indexed citations
4.
Goodwin, Michael M.. (2008). Primary-ambient decomposition and dereverberation of two-channel and multichannel audio. 16. 797–800. 1 indexed citations
5.
Jot, Jean-Marc, et al.. (2007). Spatial Audio Scene Coding in a Universal Two-Channel 3-D Stereo Format. Journal of the Audio Engineering Society. 5 indexed citations
6.
Goodwin, Michael M. & Jean-Marc Jot. (2007). Binaural 3-D Audio Rendering Based on Spatial Audio Scene Coding. Journal of the Audio Engineering Society. 16 indexed citations
7.
Merimaa, Juha, Michael M. Goodwin, & Jean-Marc Jot. (2007). Correlation-Based Ambience Extraction from Stereo Recordings. Journal of the Audio Engineering Society. 25 indexed citations
8.
Goodwin, Michael M. & Carlos Avendaño. (2006). Frequency-Domain Algorithms for Audio Signal Enhancement Based on Transient Modification. Journal of the Audio Engineering Society. 54(9). 827–840. 4 indexed citations
9.
Goodwin, Michael M. & Jean-Marc Jot. (2006). Analysis and Synthesis for Universal Spatial Audio Coding. Journal of the Audio Engineering Society. 9 indexed citations
10.
Goodwin, Michael M. & Jean-Marc Jot. (2006). A Frequency-domain Framework for Spatial Audio Coding Based on Universal Spatial Cues. Journal of the Audio Engineering Society. 12 indexed citations
11.
Goodwin, Michael M.. (2006). Allpass Arrays: Theory, Design, and Applications. Journal of the Audio Engineering Society. 1 indexed citations
12.
Avendaño, Carlos & Michael M. Goodwin. (2004). Enhancement of Audio Signals Based on Modulation Spectrum Processing. Journal of the Audio Engineering Society. 1 indexed citations
13.
Goodwin, Michael M. & J. Laroche. (2004). A dynamic programming approach to audio segmentation and speech/music discrimination. 4. iv–309. 10 indexed citations
14.
Goodwin, Michael M. & Carlos Avendaño. (2003). Parametric Coding and Frequency-Domain Processing in Multichannel Audio Applications. 1 indexed citations
15.
Goodwin, Michael M. & Martin Vetterli. (2002). Atomic decompositions of audio signals. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 4–4. 9 indexed citations
16.
Goodwin, Michael M., et al.. (1998). Sound representation and modification with multiresolution sinusoidal models. The Journal of the Acoustical Society of America. 103(5_Supplement). 2757–2757. 1 indexed citations
17.
Goodwin, Michael M., et al.. (1995). Overlap-Add Synthesis of NonStationary Sinusoids.. International Computer Music Conference. 1995. 112–118. 11 indexed citations
18.
Freed, Adrian, Mark Goldstein, Michael M. Goodwin, et al.. (1994). Real-Time Additive Synthesis Controlled by a Mixture of Neural-Networks and Direct Manipulation of Physical and Perceptual Attributes. The Journal of the Abraham Lincoln Association. 1 indexed citations
19.
Goodwin, Michael M. & Gary W. Elko. (1993). Constant beamwidth beamforming. IEEE International Conference on Acoustics Speech and Signal Processing. 169–172 vol.1. 70 indexed citations
20.
Elko, Gary W. & Michael M. Goodwin. (1992). Beam Dithering: Acoustic Feedback Control Using a Modulated-Directivity Loudspeaker Array. Journal of the Audio Engineering Society. 4 indexed citations

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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