Soham Deshmukh

552 citations
14 papers · 233 indexed · 1 hit paper · h-index 6
Topics
Music and Audio Processing (10 papers)Speech and Audio Processing (6 papers)Speech Recognition and Synthesis (6 papers)
Journals
Scientific ReportsarXiv (Cornell University)Proceedings of the AAAI Conference on Artificial Intelligence

In The Last Decade

Soham Deshmukh

13 papers receiving 221 citations

Hit Papers

CLAP Learning Audio Concepts from Natural Language Superv...202320262024202520234080120

Peers

Soham Deshmukh
Comparison fields: 5 of 42
  • Signal Processing 144
  • Artificial Intelligence 122
  • Computer Vision and Pattern Recognition 67
  • Experimental and Cognitive Psychology 19
  • Radiology, Nuclear Medicine and Imaging 14
Replace Mahmoud Al Ismail with:
Mahmoud Al Ismail United States
Helin Wang China
Xinjian Li United States
Kevin Kilgour Germany
Ziqiang Shi China
Xu Xiang China
Emiru Tsunoo United States
Toru Nakashika Japan
Yasunori Ohishi Japan
Soham Deshmukh relative to Mahmoud Al Ismail United States Mahmoud Al Ismail's profile →
Citations per field
00.5×1.5×
Mahmoud Al Ismail · 1×
Citations per year

Countries citing papers authored by Soham Deshmukh

Since Specialization
Citations

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

Fields of papers citing papers by Soham Deshmukh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soham Deshmukh

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 3
2 1
3 1
4 1
5 20
6 2
7 0
8 7
9 4
10
CLAP Learning Audio Concepts from Natural Language Supervisionbreakdown →
149
11 19
12 2
13 18
14 6

About Soham Deshmukh

Soham Deshmukh is a scholar working on Signal Processing, Developmental Biology and Music, having authored 14 papers that have together received 233 indexed citations. Recurring topics across this work include Music and Audio Processing (10 papers), Speech and Audio Processing (6 papers) and Speech Recognition and Synthesis (6 papers). The work is most often cited by research in Signal Processing (144 citations), Artificial Intelligence (122 citations) and Computer Vision and Pattern Recognition (67 citations). Soham Deshmukh has collaborated with scholars based in United Kingdom, United States and United Arab Emirates. Frequent co-authors include Benjamin Elizalde, Mahmoud Al Ismail, Huaming Wang, Rita Singh, Bhiksha Raj, Dimitra Emmanouilidou, Hannes Gamper, Zhongqi Miao, Huaming Wang and Rahul Dodhia. Their work appears in journals such as Scientific Reports, arXiv (Cornell University) 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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