Hemlata Tak
- Signal Processing top 1%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Physiology
- Pharmacy
- Co-authors
- Massimiliano TodiscoJosé PatinoNicholas EvansAndreas NautschAnthony LarcherMadhu R. KambleJee-weon JungHa-Jin Yu
- Topics
- Speech Recognition and Synthesis (12 papers)Speech and Audio Processing (11 papers)Music and Audio Processing (6 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceSpeech CommunicationHAL (Le Centre pour la Communication Scientifique Directe)
In The Last Decade
Hemlata Tak
19 papers receiving 561 citations
Hit Papers
Peers
Comparison fields: 5 of 37
- Signal Processing 472
- Artificial Intelligence 461
- Computer Vision and Pattern Recognition 182
- Physiology 51
- Pharmacy 15
Countries citing papers authored by Hemlata Tak
This map shows the geographic impact of Hemlata Tak'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 Hemlata Tak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hemlata Tak more than expected).
Fields of papers citing papers by Hemlata Tak
This network shows the impact of papers produced by Hemlata Tak. 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 Hemlata Tak. The network helps show where Hemlata Tak may publish in the future.
Co-authorship network of co-authors of Hemlata Tak
This figure shows the co-authorship network connecting the top 25 collaborators of Hemlata Tak. A scholar is included among the top collaborators of Hemlata Tak 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 Hemlata Tak. Hemlata Tak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 15 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 5 | |
| 8 | 5 | |
| 9 | 26 | |
| 10 | AASIST: Audio Anti-Spoofing Using Integrated Spectro-Temporal Graph Attention Networksbreakdown → | 156 |
| 11 | 44 | |
| 12 | 1 | |
| 13 | End-to-End anti-spoofing with RawNet2breakdown → | 191 |
| 14 | 40 | |
| 15 | 16 | |
| 16 | 23 | |
| 17 | 3 | |
| 18 | 21 | |
| 19 | 40 |
About Hemlata Tak
Hemlata Tak is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 592 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (12 papers), Speech and Audio Processing (11 papers) and Music and Audio Processing (6 papers). The work is most often cited by research in Signal Processing (472 citations), Artificial Intelligence (461 citations) and Computer Vision and Pattern Recognition (182 citations). Hemlata Tak has collaborated with scholars based in France, India and Finland. Frequent co-authors include Massimiliano Todisco, José Patino, Nicholas Evans, Andreas Nautsch, Anthony Larcher, Nicholas Evans, Madhu R. Kamble, Jee-weon Jung, Ha-Jin Yu and Hee-Soo Heo. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Speech Communication and HAL (Le Centre pour la Communication Scientifique Directe).
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.