Sudhamay Maity

479 total citations
10 papers, 230 citations indexed

About

Sudhamay Maity is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sudhamay Maity has authored 10 papers receiving a total of 230 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Signal Processing and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sudhamay Maity's work include Speech Recognition and Synthesis (7 papers), Speech and Audio Processing (5 papers) and Music and Audio Processing (5 papers). Sudhamay Maity is often cited by papers focused on Speech Recognition and Synthesis (7 papers), Speech and Audio Processing (5 papers) and Music and Audio Processing (5 papers). Sudhamay Maity collaborates with scholars based in India, Australia and United States. Sudhamay Maity's co-authors include K. Sreenivasa Rao, V. Ramu Reddy, Shashidhar G. Koolagudi, Anil Kumar Vuppala, Dipanjan Nandi, N. P. Narendra and Kanishka Rao and has published in prestigious journals such as Expert Systems with Applications, International Journal of Speech Technology and ACM Transactions on Asian and Low-Resource Language Information Processing.

In The Last Decade

Sudhamay Maity

8 papers receiving 221 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sudhamay Maity India	7	188	174	55	30	11	10	230
Nirmesh J. Shah India	9	189 1.0×	134 0.8×	73 1.3×	30 1.0×	5 0.5×	26	233
Efthymios Tzinis United States	10	145 0.8×	194 1.1×	54 1.0×	28 0.9×	7 0.6×	19	265
Subhadeep Dey Switzerland	10	248 1.3×	232 1.3×	78 1.4×	39 1.3×	6 0.5×	20	320
Mahesh Kumar Nandwana United States	11	242 1.3×	248 1.4×	19 0.3×	25 0.8×	10 0.9×	22	303
Toshiaki Fukada Japan	7	346 1.8×	290 1.7×	49 0.9×	43 1.4×	5 0.5×	17	378
Julien Karadayi France	7	333 1.8×	190 1.1×	32 0.6×	21 0.7×	8 0.7×	10	389
Aitor Álvarez Spain	8	120 0.6×	88 0.5×	25 0.5×	56 1.9×	4 0.4×	28	201
Yongguo Kang China	5	166 0.9×	124 0.7×	93 1.7×	21 0.7×	8 0.7×	6	208
Tomoki Koriyama Japan	10	320 1.7×	247 1.4×	50 0.9×	22 0.7×	3 0.3×	51	379
Yiqin Zhao United States	7	102 0.5×	156 0.9×	168 3.1×	45 1.5×	4 0.4×	13	251

Countries citing papers authored by Sudhamay Maity

Since Specialization

Citations

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

Fields of papers citing papers by Sudhamay Maity

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sudhamay Maity

This figure shows the co-authorship network connecting the top 25 collaborators of Sudhamay Maity. A scholar is included among the top collaborators of Sudhamay Maity 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 Sudhamay Maity. Sudhamay Maity is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Maity, Sudhamay, et al.. (2023). IIITH-CSTD Corpus: Crowdsourced Strategies for the Collection of a Large-scale Telugu Speech Corpus. ACM Transactions on Asian and Low-Resource Language Information Processing. 22(7). 1–26.

2.

Rao, K. Sreenivasa, V. Ramu Reddy, & Sudhamay Maity. (2015). Language Identification Using Spectral and Prosodic Features. Springer briefs in electrical and computer engineering. 22 indexed citations

3.

Rao, K. Sreenivasa, Sudhamay Maity, & V. Ramu Reddy. (2013). Pitch synchronous and glottal closure based speech analysis for language recognition. International Journal of Speech Technology. 16(4). 413–430. 24 indexed citations

4.

Reddy, V. Ramu, Sudhamay Maity, & K. Sreenivasa Rao. (2013). Identification of Indian languages using multi-level spectral and prosodic features. International Journal of Speech Technology. 16(4). 489–511. 58 indexed citations

5.

Rao, Kanishka, et al.. (2012). Segmentation of TV broadcast news using speaker specific information. 1–5.

6.

Maity, Sudhamay, Anil Kumar Vuppala, K. Sreenivasa Rao, & Dipanjan Nandi. (2012). IITKGP-MLILSC speech database for language identification. 1–5. 41 indexed citations

7.

Narendra, N. P., et al.. (2011). Development of Bengali screen reader using Festival speech synthesizer. 1–4. 2 indexed citations

8.

Rao, K. Sreenivasa, et al.. (2011). Recognition of emotions from video using neural network models. Expert Systems with Applications. 38(10). 13181–13185. 23 indexed citations

9.

Narendra, N. P., et al.. (2011). Development of syllable-based text to speech synthesis system in Bengali. International Journal of Speech Technology. 14(3). 167–181. 41 indexed citations

10.

Rao, K. Sreenivasa, et al.. (2010). Characterization of emotions using the dynamics of prosodic features. paper 941–0. 19 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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