Yaman Kumar

549 citations
24 papers · 155 · h-index 7

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Hate Speech and Cyberbullying Detection
    • Speech Recognition and Synthesis
    • Text Readability and Simplification
    • Speech and Audio Processing
    • Music and Audio Processing

Papers in

Yaman Kumar

21 papers receiving 140 citations

Peers

Yaman Kumar
Comparison fields: 5 of 39
  • Artificial Intelligence 111
  • Signal Processing 34
  • Computer Science Applications 13
  • Health Informatics 2
  • Human-Computer Interaction 7
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Citations per field
00.5×1.5×2.3×
Andrew Caines · 1×
Citations per year

Countries citing papers authored by Yaman Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Yaman Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yaman Kumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yaman Kumar Line = papers co-authored together Yaman Kumar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201938
2 201920
3 202210
4 202310
5 201810
6 20197
7 20236
8 20236
9 20196
10 20196
11 20235
12 20225
13 20195
14 20195
15 20224
16
An Annotated Dataset of Discourse Modes in Hindi Stories
20203
17 20233
18 20222
19 20222
20 20231

About Yaman Kumar

Yaman Kumar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Information Systems and Sociology and Political Science, having authored 24 papers that have together received 155 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers), Music and Audio Processing (4 papers), Speech and Audio Processing (4 papers), Multimodal Machine Learning Applications (3 papers), Speech Recognition and Synthesis (3 papers), Sentiment Analysis and Opinion Mining (2 papers) and Speech and dialogue systems (2 papers). The work is most often cited by research in Artificial Intelligence (111 citations), Signal Processing (34 citations), Computer Science Applications (13 citations), Health Informatics (2 citations) and Human-Computer Interaction (7 citations). Yaman Kumar has collaborated with scholars based in India, United States and Singapore. Frequent co-authors include Rajiv Ratn Shah, Debanjan Mahata, Roger Zimmermann, Changyou Chen, Swati Aggarwal, Ponnurangam Kumaraguru, Haimin Zhang, Balaji Krishnamurthy, Karan Uppal and Nora Hollenstein. Their work appears in journals such as International Journal of Artificial Intelligence in Education, Language Resources and Evaluation, Interspeech 2022 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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