Preethi Jyothi

1.3k total citations
78 papers, 484 citations indexed

About

Preethi Jyothi is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Preethi Jyothi has authored 78 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Artificial Intelligence, 24 papers in Signal Processing and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Preethi Jyothi's work include Speech Recognition and Synthesis (45 papers), Natural Language Processing Techniques (31 papers) and Speech and Audio Processing (21 papers). Preethi Jyothi is often cited by papers focused on Speech Recognition and Synthesis (45 papers), Natural Language Processing Techniques (31 papers) and Speech and Audio Processing (21 papers). Preethi Jyothi collaborates with scholars based in India, United States and United Kingdom. Preethi Jyothi's co-authors include Mark Hasegawa‐Johnson, Eric Fosler‐Lussier, Abhinav Jain, Karen Livescu, Sunita Sarawagi, Rohit Prabhavalkar, Vihari Piratla, Shiv Shankar, Yanzhang He and Soumen Chakrabarti and has published in prestigious journals such as Proceedings of the IEEE, Language Resources and Evaluation and Computer Speech & Language.

In The Last Decade

Preethi Jyothi

63 papers receiving 447 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Preethi Jyothi India 12 415 198 65 58 17 78 484
Victor Abrash United States 11 471 1.1× 217 1.1× 38 0.6× 64 1.1× 5 0.3× 25 527
M. Bisani Germany 9 795 1.9× 232 1.2× 85 1.3× 39 0.7× 7 0.4× 11 844
Teemu Hirsimäki Finland 12 586 1.4× 130 0.7× 33 0.5× 31 0.5× 5 0.3× 20 648
Fabio Brugnara Italy 12 592 1.4× 405 2.0× 73 1.1× 120 2.1× 6 0.4× 44 673
Laurent Besacier France 15 523 1.3× 178 0.9× 148 2.3× 30 0.5× 4 0.2× 73 665
Beatrice T. Oshika United States 8 364 0.9× 251 1.3× 30 0.5× 78 1.3× 4 0.2× 20 416
Sebastian Stüker Germany 17 885 2.1× 274 1.4× 121 1.9× 39 0.7× 9 0.5× 69 931
Tim Schlippe Germany 13 435 1.0× 124 0.6× 25 0.4× 55 0.9× 11 0.6× 41 516
Josef Psutka Czechia 11 385 0.9× 187 0.9× 52 0.8× 34 0.6× 3 0.2× 54 457
Javier Latorre United Kingdom 13 497 1.2× 377 1.9× 51 0.8× 71 1.2× 20 1.2× 35 554

Countries citing papers authored by Preethi Jyothi

Since Specialization
Citations

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

Fields of papers citing papers by Preethi Jyothi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Preethi Jyothi

This figure shows the co-authorship network connecting the top 25 collaborators of Preethi Jyothi. A scholar is included among the top collaborators of Preethi Jyothi 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 Preethi Jyothi. Preethi Jyothi 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.
Jyothi, Preethi, et al.. (2025). Design an Optimization Based Ensemble CNN Technique to Classify the Various Stages of Skin Cancer. Journal of Neonatal Surgery. 14(7S). 471–490.
2.
Jyothi, Preethi, et al.. (2024). ORGANIZATION, PURPOSE, AND VALUES. 1 indexed citations
3.
4.
5.
Kumar, Sanjeev, Preethi Jyothi, & Pushpak Bhattacharyya. (2024). Part-of-speech Tagging for Extremely Low-resource Indian Languages. 14422–14431.
6.
Jyothi, Preethi, et al.. (2024). In-context Mixing (ICM): Code-mixed Prompts for Multilingual LLMs. 4162–4176. 1 indexed citations
7.
Jyothi, Preethi, et al.. (2023). Improving Pretraining Techniques for Code-Switched NLP. 1176–1191.
8.
Sarawagi, Sunita, et al.. (2023). Speech-enriched Memory for Inference-time Adaptation of ASR Models to Word Dictionaries. 14820–14835. 1 indexed citations
9.
Jyothi, Preethi, et al.. (2022). CoCoa: An Encoder-Decoder Model for Controllable Code-switched Generation. 2466–2479. 2 indexed citations
10.
11.
Singh, Ankita, Srinivasa Raghavan, Saurabh Vyas, et al.. (2021). MUCS 2021: Multilingual and Code-Switching ASR Challenges for Low Resource Indian Languages. arXiv (Cornell University). 2446–2450. 33 indexed citations
12.
Bali, Kalika, et al.. (2020). Crowdsourcing Speech Data for Low-Resource Languages from Low-Income Workers. Language Resources and Evaluation. 2819–2826. 10 indexed citations
13.
Shankar, Shiv, Vihari Piratla, Soumen Chakrabarti, et al.. (2018). Generalizing Across Domains via Cross-Gradient Training. International Conference on Learning Representations. 38 indexed citations
14.
Jain, Abhinav, et al.. (2018). Improved Accented Speech Recognition Using Accent Embeddings and Multi-task Learning. 2454–2458. 55 indexed citations
15.
Siddhant, Aditya, Preethi Jyothi, & Sriram Ganapathy. (2017). Leveraging native language speech for accent identification using deep Siamese networks. arXiv (Cornell University). 621–628. 8 indexed citations
16.
Chen, Wenda, Mark Hasegawa‐Johnson, Nancy F. Chen, Preethi Jyothi, & Lav R. Varshney. (2016). Clustering-based Phonetic Projection in Mismatched Crowdsourcing Channels for Low-resourced ASR.. International Conference on Computational Linguistics. 133–141.
17.
Cole, Jennifer, et al.. (2015). Prosodic and structural correlates of perceived prominence in Russian and Hindi.. ICPhS. 6 indexed citations
18.
Jyothi, Preethi, et al.. (2014). Modeling and Implementation of Wireless Embedded Robot Arm for Object Sorting. IOSR Journal of Electrical and Electronics Engineering. 9(4). 35–44. 2 indexed citations
19.
Jyothi, Preethi, Leif Johnson, Ciprian Chelba, & Brian Strope. (2012). Large-scale discriminative language model reranking for voice-search. North American Chapter of the Association for Computational Linguistics. 41–49. 3 indexed citations
20.
Prabhavalkar, Rohit, et al.. (2010). Investigations into the Crandem Approach to Word Recognition. North American Chapter of the Association for Computational Linguistics. 725–728. 2 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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