Bunlong Lay

414 citations
9 papers · 210 · 1 hit paper · h-index 6

Impact in

    • Speech and Audio Processing
    • Music and Audio Processing
    • Blind Source Separation Techniques
    • Speech Recognition and Synthesis
    • Wireless Signal Modulation Classification

Papers in

Bunlong Lay

8 papers receiving 191 citations

Bunlong Lay's Hit Papers

Speech Enhancement and Dereverberation With Diffusion-Based Generative Models 2023 · 137 citations
1370+1+2Years since publication4080120

Peers

Bunlong Lay
Comparison fields: 5 of 27
  • Signal Processing 157
  • Artificial Intelligence 119
  • Pharmacy 8
  • Computational Mechanics 29
  • Computer Vision and Pattern Recognition 20
Replace Jean-Marie Lemercier with:
Jean-Marie Lemercier Germany
Sherif Abdulatif Germany
Simon Welker Germany
Yang Ai China
Yanhua Long China
Steffen Zeiler Germany
Mahesh Kumar Nandwana United States
Kouhei Sekiguchi Japan
Ju Lin United States
Bunlong Lay relative to Jean-Marie Lemercier Germany Jean-Marie Lemercier's profile →
Citations per field
00.5×1.5×
Jean-Marie Lemercier · 1×
Citations per year

Countries citing papers authored by Bunlong Lay

Since Specialization
Citations

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

Fields of papers citing papers by Bunlong Lay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Bunlong Lay, 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 Bunlong Lay Line = papers co-authored together Bunlong Lay links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
Speech Enhancement and Dereverberation With Diffusion-Based Generative Models
Hit paper breakdown →
2023137
2 202419
3 202316
4 202014
5 202410
6 20247
7 20234
8 20242
9 20241

About Bunlong Lay

Bunlong Lay is a scholar working on Signal Processing, Artificial Intelligence, Pharmacy, Ocean Engineering and Computational Mechanics, having authored 9 papers that have together received 210 indexed citations. Recurring topics across this work include Speech and Audio Processing (8 papers), Music and Audio Processing (4 papers), Speech Recognition and Synthesis (3 papers), Infant Health and Development (2 papers), Wireless Signal Modulation Classification (1 paper), Geophysical Methods and Applications (1 paper), Advanced SAR Imaging Techniques (1 paper) and Emotion and Mood Recognition (1 paper). The work is most often cited by research in Signal Processing (157 citations), Artificial Intelligence (119 citations), Pharmacy (8 citations), Computational Mechanics (29 citations) and Computer Vision and Pattern Recognition (20 citations). Bunlong Lay has collaborated with scholars based in Germany. Frequent co-authors include Timo Gerkmann, Julius Richter, Simon Welker, Jean-Marie Lemercier, Alexander Charlish, Shinji Watanabe, Alexander Richard and Nale Lehmann‐Willenbrock. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, IEEE Open Journal of Signal Processing and Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft).

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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