M. Berouti

1.6k citations
17 papers · 921 · 1 hit paper · h-index 7

Impact in

Papers in

M. Berouti

12 papers receiving 821 citations

M. Berouti's Hit Papers

Enhancement of speech corrupted by acoustic noise 2005 · 736 citations
7360+7+14Years since publication200400600

Peers

M. Berouti
Comparison fields: 5 of 59
  • Signal Processing 826
  • Computational Mechanics 454
  • Computer Vision and Pattern Recognition 196
  • Artificial Intelligence 303
  • Cognitive Neuroscience 158
Replace Andrew Varga with:
Andrew Varga United Kingdom
Hans‐Günter Hirsch Germany
A. Alwan United States
Kamil Wójcicki Australia
Baruch Berdugo Israel
Athanasios Mouchtaris Greece
Pejman Mowlaee Austria
Soundararajan Srinivasan United States
C. A. McGonegal United States
M. Berouti relative to Andrew Varga United Kingdom Andrew Varga's profile →
Citations per field
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Andrew Varga · 1×
Citations per year

Countries citing papers authored by M. Berouti

Since Specialization
Citations

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

Fields of papers citing papers by M. Berouti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside M. Berouti, 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 M. Berouti Line = papers co-authored together M. Berouti links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1
Enhancement of speech corrupted by acoustic noise
Hit paper breakdown →
2005736
2 200572
3 197955
4 19798
5 20058
6 19787
7 20056
8 20056
9 20056
10
Estimation of glottal volume-velocity by the linear prediction inverse-filter
19764
11 20054
12 19794
13 20052
14 20052
15 20051
16 20050
17 20050

About M. Berouti

M. Berouti is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics and Physiology, having authored 17 papers that have together received 921 indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (12 papers), Speech and Audio Processing (11 papers), Advanced Adaptive Filtering Techniques (6 papers), Speech Recognition and Synthesis (5 papers), Voice and Speech Disorders (3 papers), Digital Filter Design and Implementation (3 papers), Phonetics and Phonology Research (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Signal Processing (826 citations), Computational Mechanics (454 citations), Computer Vision and Pattern Recognition (196 citations), Artificial Intelligence (303 citations) and Cognitive Neuroscience (158 citations). M. Berouti has collaborated with scholars based in United States and Canada. Frequent co-authors include J. Makhoul, John Makhoul, D. G. Childers, S. Roucos, Richard Schwartz, P. Mermelstein, P. Kabal, Alan L. Higgins, V. Viswanathan and W. Russell. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Transactions on Acoustics Speech and Signal Processing and University of Florida Digital Collections (University of Florida).

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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