Vikramjit Mitra

2.0k total citations
84 papers, 1.4k citations indexed

About

Vikramjit Mitra is a scholar working on Artificial Intelligence, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, Vikramjit Mitra has authored 84 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Artificial Intelligence, 64 papers in Signal Processing and 27 papers in Experimental and Cognitive Psychology. Recurrent topics in Vikramjit Mitra's work include Speech Recognition and Synthesis (62 papers), Speech and Audio Processing (58 papers) and Music and Audio Processing (41 papers). Vikramjit Mitra is often cited by papers focused on Speech Recognition and Synthesis (62 papers), Speech and Audio Processing (58 papers) and Music and Audio Processing (41 papers). Vikramjit Mitra collaborates with scholars based in United States, South Korea and Argentina. Vikramjit Mitra's co-authors include Carol Espy-Wilson, Horacio Franco, Martin Graciarena, Hosung Nam, Chia-Jiu Wang, Satarupa Banerjee, Elliot Saltzman, Ganesh Sivaraman, Louis Goldstein and Jane Metcalf and has published in prestigious journals such as Scientific Reports, The Journal of the Acoustical Society of America and Applied Soft Computing.

In The Last Decade

Vikramjit Mitra

83 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vikramjit Mitra United States 22 917 778 380 128 83 84 1.4k
Jun Deng Germany 20 806 0.9× 724 0.9× 770 2.0× 346 2.7× 81 1.0× 44 1.5k
Lijiang Chen China 8 312 0.3× 477 0.6× 516 1.4× 173 1.4× 44 0.5× 19 973
Norihide Kitaoka Japan 17 547 0.6× 445 0.6× 105 0.3× 176 1.4× 92 1.1× 165 987
Dimitrios Ververidis Greece 15 572 0.6× 711 0.9× 815 2.1× 358 2.8× 117 1.4× 24 1.4k
Shashidhar G. Koolagudi India 24 784 0.9× 1.1k 1.4× 885 2.3× 481 3.8× 117 1.4× 135 2.2k
Kun Han China 15 708 0.8× 999 1.3× 471 1.2× 215 1.7× 48 0.6× 35 1.4k
Ziping Zhao China 22 422 0.5× 353 0.5× 683 1.8× 150 1.2× 190 2.3× 64 1.2k
K. Sri Rama Murty India 14 1.1k 1.2× 1.1k 1.5× 316 0.8× 177 1.4× 14 0.2× 58 1.5k
Sunil Kumar Kopparapu India 17 489 0.5× 416 0.5× 237 0.6× 196 1.5× 24 0.3× 107 955
Mustaqeem Mustaqeem South Korea 15 614 0.7× 718 0.9× 765 2.0× 396 3.1× 64 0.8× 16 1.6k

Countries citing papers authored by Vikramjit Mitra

Since Specialization
Citations

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

Fields of papers citing papers by Vikramjit Mitra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vikramjit Mitra

This figure shows the co-authorship network connecting the top 25 collaborators of Vikramjit Mitra. A scholar is included among the top collaborators of Vikramjit Mitra 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 Vikramjit Mitra. Vikramjit Mitra 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.
2.
Kral, Tammi R. A., Helen Y. Weng, Vikramjit Mitra, et al.. (2023). Slower respiration rate is associated with higher self-reported well-being after wellness training. Scientific Reports. 13(1). 15953–15953. 9 indexed citations
3.
Mitra, Vikramjit, et al.. (2020). Detecting Emotion Primitives from Speech and Their Use in Discerning Categorical Emotions. 7164–7168. 9 indexed citations
4.
Yılmaz, Emre, Vikramjit Mitra, Chris Bartels, & Horacio Franco. (2018). Articulatory Features for ASR of Pathological Speech. Radboud Repository (Radboud University). 2958–2962. 11 indexed citations
5.
Hout, Julien van, Vikramjit Mitra, Horacio Franco, Chris Bartels, & Dimitra Vergyri. (2017). Tackling unseen acoustic conditions in query-by-example search using time and frequency convolution for multilingual deep bottleneck features. 48–54. 3 indexed citations
6.
Ferrer, Luciana, Martin Graciarena, & Vikramjit Mitra. (2016). A phonetically aware system for speech activity detection. 5710–5714. 10 indexed citations
7.
Mitra, Vikramjit, Wen Wang, Chris Bartels, et al.. (2016). Fusion Strategies for Robust Speech Recognition and Keyword Spotting for Channel- and Noise-Degraded Speech. 3683–3687. 4 indexed citations
8.
Vergyri, Dimitra, Elizabeth Shriberg, Vikramjit Mitra, et al.. (2015). Speech-based assessment of PTSD in a military population using diverse feature classes. 3729–3733. 15 indexed citations
9.
Hori, Takaaki, Zhuo Chen, Hakan Erdoğan, et al.. (2015). The MERL/SRI system for the 3RD CHiME challenge using beamforming, robust feature extraction, and advanced speech recognition. 22. 475–481. 30 indexed citations
10.
Mitra, Vikramjit, Wen Wang, Horacio Franco, et al.. (2014). Evaluating robust features on deep neural networks for speech recognition in noisy and channel mismatched conditions. 895–899. 31 indexed citations
11.
Mitra, Vikramjit, Mitchell McLaren, Horacio Franco, Martin Graciarena, & Nicolas Scheffer. (2013). Modulation features for noise robust speaker identification. 3703–3707. 21 indexed citations
12.
Mitra, Vikramjit, Wen Wang, Andreas Stolcke, et al.. (2013). Articulatory features for large vocabulary speech recognition. International Conference on Acoustics, Speech, and Signal Processing. 7145–7149. 5 indexed citations
13.
Mitra, Vikramjit, Hosung Nam, Carol Espy-Wilson, Elliot Saltzman, & Louis Goldstein. (2011). Speech inversion: Benefits of tract variables over pellet trajectories. 5188–5191. 5 indexed citations
14.
Mitra, Vikramjit, Hosung Nam, & Carol Espy-Wilson. (2011). Robust speech recognition using articulatory gestures in a Dynamic Bayesian Network framework. 18. 131–136. 8 indexed citations
15.
Mitra, Vikramjit, Hosung Nam, Carol Espy-Wilson, Elliot Saltzman, & Louis Goldstein. (2010). Retrieving Tract Variables From Acoustics: A Comparison of Different Machine Learning Strategies. IEEE Journal of Selected Topics in Signal Processing. 4(6). 1027–1045. 40 indexed citations
16.
Mitra, Vikramjit, Hosung Nam, Carol Espy-Wilson, Elliot Saltzman, & Louis Goldstein. (2009). Noise robustness of tract variables and their application to speech recognition. 2759–2762. 7 indexed citations
17.
Mitra, Vikramjit, İbrahim Yücel Özbek, Hosung Nam, Xin‐Hui Zhou, & Carol Espy-Wilson. (2009). From acoustics to Vocal Tract time functions. OpenMETU (Middle East Technical University). 13. 4497–4500. 10 indexed citations
18.
Mitra, Vikramjit & Chia-Jiu Wang. (2007). Content based audio classification: a neural network approach. Soft Computing. 12(7). 639–646. 11 indexed citations
19.
Mitra, Vikramjit, et al.. (2007). A Neural Network based Audio Content Classification. IEEE International Conference on Neural Networks. 1494–1499. 10 indexed citations
20.
Mitra, Vikramjit, Chia-Jiu Wang, & Satarupa Banerjee. (2006). Lidar detection of underwater objects using a neuro-SVM-based architecture. IEEE Transactions on Neural Networks. 17(3). 717–731. 65 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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