John R. Hershey

96 papers receiving 4.5k citations

Hit Papers

Approximating the Kullback Leibler Divergence Between Gau...2007202620132019200720172015200400600

Peers

John R. Hershey
Comparison fields: 5 of 127
  • Signal Processing 3.6k
  • Artificial Intelligence 3.0k
  • Computational Mechanics 850
  • Computer Vision and Pattern Recognition 550
  • Cognitive Neuroscience 429
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Citations per year

Countries citing papers authored by John R. Hershey

Since Specialization
Citations

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

Fields of papers citing papers by John R. Hershey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John R. Hershey. 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 John R. Hershey. The network helps show where John R. Hershey may publish in the future.

Co-authorship network of co-authors of John R. Hershey

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 4
3
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds
2
4 20
5
Unsupervised Sound Separation Using Mixture Invariant Training
8
6 40
7 217
8 79
9 93
10
Hybrid CTC/Attention Architecture for End-to-End Speech Recognitionbreakdown →
483
11 216
12 77
13
Statistical Dialogue Management using Intention Dependency Graph
3
14 31
15
The Iroquois Model: Using Temporal Dynamics to Separate Speakers
7
16
Model-based fusion of bone and air sensors for speech enhancement and robust speech recognition.
9
17
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters
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18 5
19
Audio-Visual Sound Separation Via Hidden Markov Models
41
20
Audio Vision: Using Audio-Visual Synchrony to Locate Sounds
157

About John R. Hershey

John R. Hershey is a scholar working on Signal Processing, Artificial Intelligence and Computational Mathematics, having authored 102 papers that have together received 4.8k indexed citations. Recurring topics across this work include Speech and Audio Processing (81 papers), Speech Recognition and Synthesis (62 papers) and Music and Audio Processing (55 papers). The work is most often cited by research in Signal Processing (3.6k citations), Artificial Intelligence (3.0k citations) and Computational Mechanics (850 citations). John R. Hershey has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include Shinji Watanabe, Peder A. Olsen, Jonathan Le Roux, Takaaki Hori, Hakan Erdoğan, Zhong-Qiu Wang, Steven J. Rennie, Suyoun Kim, Tomoki Hayashi and Felix Weninger. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Signal Processing Magazine and IEEE Journal of Selected Topics in Signal Processing.

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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