S. Umesh

1.3k total citations
111 papers, 878 citations indexed

About

S. Umesh is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, S. Umesh has authored 111 papers receiving a total of 878 indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Artificial Intelligence, 87 papers in Signal Processing and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in S. Umesh's work include Speech Recognition and Synthesis (86 papers), Speech and Audio Processing (78 papers) and Music and Audio Processing (58 papers). S. Umesh is often cited by papers focused on Speech Recognition and Synthesis (86 papers), Speech and Audio Processing (78 papers) and Music and Audio Processing (58 papers). S. Umesh collaborates with scholars based in India, United States and Canada. S. Umesh's co-authors include D.J. Nelson, Leon Cohen, D.W. Tufts, Rohit Sinha, K. Sivakumar, Nitin Prasad, Shakti P. Rath, Achintya Kumar Sarkar, Mark Gales and Hermann Ney and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Signal Processing and The Journal of the Acoustical Society of America.

In The Last Decade

S. Umesh

100 papers receiving 796 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. Umesh India 17 631 595 91 85 82 111 878
Olivier Rosec France 14 325 0.5× 402 0.7× 24 0.3× 53 0.6× 95 1.2× 40 554
C. Wellekens France 12 842 1.3× 742 1.2× 34 0.4× 96 1.1× 180 2.2× 53 1.1k
Climent Nadeu Spain 20 665 1.1× 960 1.6× 101 1.1× 47 0.6× 252 3.1× 98 1.2k
J. McDonough Germany 13 655 1.0× 556 0.9× 35 0.4× 48 0.6× 69 0.8× 24 767
A. Alwan United States 14 435 0.7× 629 1.1× 82 0.9× 141 1.7× 154 1.9× 41 908
Hong-Goo Kang South Korea 17 512 0.8× 734 1.2× 84 0.9× 88 1.0× 286 3.5× 136 1.1k
Suryakanth V. Gangashetty India 14 487 0.8× 476 0.8× 18 0.2× 156 1.8× 82 1.0× 93 714
S. Shahnawazuddin India 16 541 0.9× 537 0.9× 13 0.1× 95 1.1× 111 1.4× 77 813
Mohamad Hasan Bahari Belgium 13 321 0.5× 299 0.5× 59 0.6× 41 0.5× 45 0.5× 31 465
Xiangang Li China 16 503 0.8× 373 0.6× 54 0.6× 144 1.7× 91 1.1× 64 743

Countries citing papers authored by S. Umesh

Since Specialization
Citations

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

Fields of papers citing papers by S. Umesh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Umesh. 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 S. Umesh. The network helps show where S. Umesh may publish in the future.

Co-authorship network of co-authors of S. Umesh

This figure shows the co-authorship network connecting the top 25 collaborators of S. Umesh. A scholar is included among the top collaborators of S. Umesh 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 S. Umesh. S. Umesh 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
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Umesh, S., et al.. (2017). DNN acoustic models for dysarthric speech. 1–4. 3 indexed citations
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Joshi, Vikas, Nitin Prasad, & S. Umesh. (2015). Modified Mean and Variance Normalization: Transforming to Utterance-Specific Estimates. Circuits Systems and Signal Processing. 35(5). 1593–1609. 5 indexed citations
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Joshi, Vikas, et al.. (2011). Efficient speaker and noise normalization for robust speech recognition. 2601–2604. 1 indexed citations
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Sarkar, Achintya Kumar & S. Umesh. (2010). Investigation of Speaker-Clustered UBMs based on Vocal Tract Lengths and MLLR matrices for Speaker Verification.. 13. 3 indexed citations
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Sarkar, Achintya Kumar, Shakti P. Rath, & S. Umesh. (2010). Vocal Tract Length Normalization factor based speaker-cluster UBM for speaker verification. 1–5. 2 indexed citations
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Umesh, S., et al.. (2008). Nonuniform speaker normalization using affine transformation. The Journal of the Acoustical Society of America. 124(3). 1727–1738. 2 indexed citations
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Umesh, S., et al.. (2007). Speaker-invariant features for automatic speech recognition. International Joint Conference on Artificial Intelligence. 1738–1743. 1 indexed citations
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Umesh, S., Leon Cohen, & D.J. Nelson. (2002). Improved scale-cepstral analysis in speech. 2. 637–640. 4 indexed citations
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Umesh, S., Leon Cohen, & D.J. Nelson. (2002). Frequency warping and the Mel scale. IEEE Signal Processing Letters. 9(3). 104–107. 24 indexed citations
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Umesh, S., et al.. (1999). Scale transform in speech analysis. IEEE Transactions on Speech and Audio Processing. 7(1). 40–45. 43 indexed citations
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Nelson, Douglas J., et al.. (1995). <title>Classification of digital modulation types</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2563. 125–143. 4 indexed citations
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Wilson, Elizabeth J., S. Umesh, & D.W. Tufts. (1993). Multistage neural network structure for transient detection and feature extraction. IEEE International Conference on Acoustics Speech and Signal Processing. 11. 489–492 vol.1. 2 indexed citations
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Umesh, S. & D.W. Tufts. (1992). Resolving the components of transient signals by a multistage procedure. 93. 553–556 vol.2. 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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