Anjuli Kannan

2.4k citations
13 papers · 913 indexed · 1 hit paper · h-index 11
Topics
Speech Recognition and Synthesis (8 papers)Topic Modeling (6 papers)Music and Audio Processing (5 papers)
Partner nations
United States

In The Last Decade

Anjuli Kannan

13 papers receiving 806 citations

Hit Papers

Streaming End-to-end Speech Recognition for Mobile Devices20192026202120232019100200300

Peers

Anjuli Kannan
Comparison fields: 5 of 77
  • Artificial Intelligence 778
  • Signal Processing 419
  • Computer Vision and Pattern Recognition 64
  • Information Systems 44
  • Health Informatics 29
Replace Veton Këpuska with:
Veton Këpuska United States
Kevin Leach United States
Yun-Gyung Cheong South Korea
Rowan Zellers United States
Shuo Ren China
Kai-Fu Lee United States
Daniele Falavigna Italy
Ala Saleh Alluhaidan Saudi Arabia
Markus Dürmuth Germany
Eugene Kharitonov Russia
Anjuli Kannan relative to Veton Këpuska United States Veton Këpuska's profile →
Citations per field
00.5×3.2×
Veton Këpuska · 1×
Citations per year

Countries citing papers authored by Anjuli Kannan

Since Specialization
Citations

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

Fields of papers citing papers by Anjuli Kannan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anjuli Kannan

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

All Works

13 of 13 papers shown
#WorkIndexed citations
1 27
2 107
3
Model Unit Exploration for Sequence-to-Sequence Speech Recognition.
5
4 36
5 50
6
Streaming End-to-end Speech Recognition for Mobile Devicesbreakdown →
345
7 95
8 41
9 28
10 10
11 49
12 114
13 6

About Anjuli Kannan

Anjuli Kannan is a scholar working on Signal Processing, Family Practice and Artificial Intelligence, having authored 13 papers that have together received 913 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (8 papers), Topic Modeling (6 papers) and Music and Audio Processing (5 papers). The work is most often cited by research in Signal Processing (419 citations), Artificial Intelligence (778 citations) and Health Informatics (29 citations). Anjuli Kannan has collaborated with scholars based in United States. Frequent co-authors include Tara N. Sainath, Rohit Prabhavalkar, Yonghui Wu, Ding Zhao, Golan Pundak, David Rybach, Ruoming Pang, Yuan Shangguan, Kanishka Rao and Ian McGraw. Their work appears in journals such as JAMA Internal Medicine, INFORMS Journal on Applied Analytics and arXiv (Cornell University).

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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