Mousmita Sarma
- Signal Processing top 5%
- Artificial Intelligence top 10%
- Experimental and Cognitive Psychology top 10%
- Computer Vision and Pattern Recognition
- Pharmacy
- Co-authors
- Kandarpa Kumar SarmaNagendra Kumar GoelPegah GhahremaniNajim DehakDaniel PoveyS. R. Mahadeva PrasannaLeibny Paola GarciaSanjeev Khudanpur
- Topics
- Speech Recognition and Synthesis (21 papers)Speech and Audio Processing (18 papers)Neural Networks and Applications (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaApplied Soft ComputingIEEE Intelligent Systems
- Partner nations
- India
In The Last Decade
Mousmita Sarma
27 papers receiving 204 citations
Peers
Comparison fields: 5 of 36
- Signal Processing 175
- Artificial Intelligence 157
- Experimental and Cognitive Psychology 83
- Computer Vision and Pattern Recognition 19
- Pharmacy 9
Countries citing papers authored by Mousmita Sarma
This map shows the geographic impact of Mousmita Sarma'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 Mousmita Sarma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mousmita Sarma more than expected).
Fields of papers citing papers by Mousmita Sarma
This network shows the impact of papers produced by Mousmita Sarma. 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 Mousmita Sarma. The network helps show where Mousmita Sarma may publish in the future.
Co-authorship network of co-authors of Mousmita Sarma
This figure shows the co-authorship network connecting the top 25 collaborators of Mousmita Sarma. A scholar is included among the top collaborators of Mousmita Sarma 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 Mousmita Sarma. Mousmita Sarma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | CaptionAI: A Real-Time Multilingual Captioning Application. | 0 |
| 2 | Extracting Speaker's Gender, Accent, Age and Emotional State from Speech. | 3 |
| 3 | 87 | |
| 4 | 1 | |
| 5 | 6 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 13 | |
| 9 | 10 | |
| 10 | 4 | |
| 11 | 12 | |
| 12 | 14 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 3 | |
| 16 | 1 | |
| 17 | 2 | |
| 18 | 3 | |
| 19 | 5 | |
| 20 | 8 |
About Mousmita Sarma
Mousmita Sarma is a scholar working on Signal Processing, Artificial Intelligence and Language and Linguistics, having authored 30 papers that have together received 221 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (21 papers), Speech and Audio Processing (18 papers) and Neural Networks and Applications (8 papers). The work is most often cited by research in Signal Processing (175 citations), Experimental and Cognitive Psychology (83 citations) and Artificial Intelligence (157 citations). Mousmita Sarma has collaborated with scholars based in India. Frequent co-authors include Kandarpa Kumar Sarma, Nagendra Kumar Goel, Pegah Ghahremani, Najim Dehak, Daniel Povey, S. R. Mahadeva Prasanna, Leibny Paola Garcia, Sanjeev Khudanpur, Desh Raj and Matthew Wiesner. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Soft Computing and IEEE Intelligent Systems.
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.