Om Deshmukh
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 5%
- Experimental and Cognitive Psychology top 10%
- Cognitive Neuroscience
- Co-authors
- Carol Espy-WilsonAriel SalomonSantanu ChaudhurySumit NegiAshish VermaArijit BiswasKuldeep Singh YadavAmit Juneja
- Topics
- Speech and Audio Processing (22 papers)Speech Recognition and Synthesis (18 papers)Music and Audio Processing (13 papers)
- Journals
- The Journal of the Acoustical Society of AmericaIEEE Transactions on Speech and Audio ProcessingSpeech Communication
- Partner nations
- United StatesIndiaFrance
In The Last Decade
Om Deshmukh
45 papers receiving 489 citations
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 292
- Signal Processing 204
- Computer Vision and Pattern Recognition 174
- Experimental and Cognitive Psychology 128
- Cognitive Neuroscience 38
Countries citing papers authored by Om Deshmukh
This map shows the geographic impact of Om 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 Om Deshmukh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Om Deshmukh more than expected).
Fields of papers citing papers by Om Deshmukh
This network shows the impact of papers produced by Om 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 Om Deshmukh. The network helps show where Om Deshmukh may publish in the future.
Co-authorship network of co-authors of Om Deshmukh
This figure shows the co-authorship network connecting the top 25 collaborators of Om Deshmukh. A scholar is included among the top collaborators of Om 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 Om Deshmukh. Om Deshmukh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational Videos. | 7 |
| 2 | TutorSpace: Content-centric Platform for Enabling Blended Learning in Developing Countries. | 0 |
| 3 | 9 | |
| 4 | 3 | |
| 5 | 4 | |
| 6 | Topic Transition in Educational Videos Using Visually Salient Words. | 6 |
| 7 | Acoustic stress detection for improved navigation of educational videos. | 1 |
| 8 | Discovering Concept Maps from Textual Sources. | 1 |
| 9 | 27 | |
| 10 | 6 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 33 | |
| 14 | 2 | |
| 15 | 7 | |
| 16 | 1 | |
| 17 | 3 | |
| 18 | 3 | |
| 19 | 0 | |
| 20 | 1 |
About Om Deshmukh
Om Deshmukh is a scholar working on Signal Processing, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 49 papers that have together received 525 indexed citations. Recurring topics across this work include Speech and Audio Processing (22 papers), Speech Recognition and Synthesis (18 papers) and Music and Audio Processing (13 papers). The work is most often cited by research in Signal Processing (204 citations), Experimental and Cognitive Psychology (128 citations) and Artificial Intelligence (292 citations). Om Deshmukh has collaborated with scholars based in United States, India and France. Frequent co-authors include Carol Espy-Wilson, Ariel Salomon, Santanu Chaudhury, Sumit Negi, Ashish Verma, Arijit Biswas, Kuldeep Singh Yadav, Amit Juneja, Pedro J. Moreno and Beth Logan. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Transactions on Speech and Audio Processing and Speech Communication.
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.