Siddhant Arora

427 citations
39 papers · 185 indexed · h-index 10
Topics
Speech Recognition and Synthesis (21 papers)Natural Language Processing Techniques (16 papers)Topic Modeling (14 papers)
Journals
Journal of EngineeringInternational Journal of Microbiology ResearchProceedings of the AAAI Conference on Artificial Intelligence
Partner nations
United StatesIndiaJapan

In The Last Decade

Siddhant Arora

33 papers receiving 178 citations

Peers

Siddhant Arora
Comparison fields: 5 of 24
  • Artificial Intelligence 165
  • Signal Processing 40
  • Information Systems 11
  • Computer Vision and Pattern Recognition 9
  • Experimental and Cognitive Psychology 4
Replace Huyen Nguyen with:
Huyen Nguyen United States
Solomon Teferra Abate Ethiopia
Wenxin Hou Japan
Marco Dinarelli France
Zhouxing Shi United States
Ankur Gandhe United States
Felix Kreuk Israel
Hwidong Na South Korea
Mariem Ellouze Tunisia
Brij Mohan Lal Srivastava France
Siddhant Arora relative to Huyen Nguyen United States Huyen Nguyen's profile →
Citations per field
00.5×6.7×
Huyen Nguyen · 1×
Citations per year

Countries citing papers authored by Siddhant Arora

Since Specialization
Citations

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

Fields of papers citing papers by Siddhant Arora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Siddhant Arora

This figure shows the co-authorship network connecting the top 25 collaborators of Siddhant Arora. A scholar is included among the top collaborators of Siddhant Arora 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 Siddhant Arora. Siddhant Arora 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
#WorkIndexed citations
1 0
2 1
3 1
4 9
5 1
6 0
7 0
8 0
9 3
10 2
11 1
12 12
13 1
14 9
15 1
16 9
17 14
18 1
19 7
20
Understanding Community Rivalry on Social Media: A Case Study of Two Footballing Giants.
0

About Siddhant Arora

Siddhant Arora is a scholar working on Computational Mathematics, Artificial Intelligence and Signal Processing, having authored 39 papers that have together received 185 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (21 papers), Natural Language Processing Techniques (16 papers) and Topic Modeling (14 papers). The work is most often cited by research in Artificial Intelligence (165 citations), Signal Processing (40 citations) and Computer Science Applications (3 citations). Siddhant Arora has collaborated with scholars based in United States, India and Japan. Frequent co-authors include Shinji Watanabe, Yifan Peng, Xuankai Chang, Siddharth Dalmia, Alan W. Black, Sujay V. Kumar, Ngoc Thang Vu, Yosuke Higuchi, Jiatong Shi and Yuekai Zhang. Their work appears in journals such as Journal of Engineering, International Journal of Microbiology Research and Proceedings of the AAAI Conference on Artificial Intelligence.

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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