Umit Yapanel

4.2k total citations · 1 hit paper
25 papers, 3.1k citations indexed

About

Umit Yapanel is a scholar working on Artificial Intelligence, Signal Processing and Pharmacy. According to data from OpenAlex, Umit Yapanel has authored 25 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 13 papers in Signal Processing and 7 papers in Pharmacy. Recurrent topics in Umit Yapanel's work include Speech Recognition and Synthesis (14 papers), Speech and Audio Processing (11 papers) and Music and Audio Processing (7 papers). Umit Yapanel is often cited by papers focused on Speech Recognition and Synthesis (14 papers), Speech and Audio Processing (11 papers) and Music and Audio Processing (7 papers). Umit Yapanel collaborates with scholars based in United States and Austria. Umit Yapanel's co-authors include Dongxin Xu, Jeffrey A. Richards, Frederick J. Zimmerman, Dimitri Christakis, Michelle M. Garrison, Jill Gilkerson, Sharmistha Gray, John H. L. Hansen, Steven F. Warren and D. Kimbrough Oller and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PEDIATRICS and Journal of Autism and Developmental Disorders.

In The Last Decade

Umit Yapanel

24 papers receiving 2.9k citations

Hit Papers

A Population-Based Study 2009 2026 2014 2020 2009 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Umit Yapanel United States 15 666 453 397 365 348 25 3.1k
Dongxin Xu United States 20 729 1.1× 474 1.0× 337 0.8× 367 1.0× 358 1.0× 57 3.2k
Catherine M. Hill United Kingdom 32 168 0.3× 290 0.6× 630 1.6× 109 0.3× 387 1.1× 127 3.0k
R. H. Largo Switzerland 40 589 0.9× 324 0.7× 867 2.2× 400 1.1× 357 1.0× 114 6.0k
Risto Bloigu Finland 39 141 0.2× 217 0.5× 847 2.1× 394 1.1× 503 1.4× 157 5.2k
Robert Heard Australia 24 245 0.4× 44 0.1× 263 0.7× 133 0.4× 291 0.8× 88 2.1k
Kevin Norton Australia 33 914 1.4× 67 0.1× 84 0.2× 173 0.5× 198 0.6× 132 5.5k
Daisy Elliott United Kingdom 28 130 0.2× 102 0.2× 572 1.4× 457 1.3× 405 1.2× 99 2.7k
Joanne Crawford United Kingdom 24 409 0.6× 90 0.2× 1.2k 3.0× 189 0.5× 446 1.3× 57 3.5k
Noelle E. Carlozzi United States 35 176 0.3× 80 0.2× 578 1.5× 232 0.6× 627 1.8× 199 4.7k
Martin Doherty United Kingdom 31 953 1.4× 241 0.5× 708 1.8× 211 0.6× 78 0.2× 77 2.7k

Countries citing papers authored by Umit Yapanel

Since Specialization
Citations

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

Fields of papers citing papers by Umit Yapanel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Umit Yapanel

This figure shows the co-authorship network connecting the top 25 collaborators of Umit Yapanel. A scholar is included among the top collaborators of Umit Yapanel 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 Umit Yapanel. Umit Yapanel 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
1.
Richards, Jeffrey A., Dongxin Xu, Jill Gilkerson, et al.. (2017). Automated Assessment of Child Vocalization Development Using LENA. Journal of Speech Language and Hearing Research. 60(7). 2047–2063. 19 indexed citations
2.
Yapanel, Umit, et al.. (2012). GMM-Based Efficient Language Identification.
3.
Oller, D. Kimbrough, Partha Niyogi, Sharmistha Gray, et al.. (2010). Automated vocal analysis of naturalistic recordings from children with autism, language delay, and typical development. Proceedings of the National Academy of Sciences. 107(30). 13354–13359. 265 indexed citations
4.
Xu, Dongxin, Jeffrey A. Richards, Jill Gilkerson, et al.. (2009). Automatic childhood autism detection by vocalization decomposition with phone-like units. 1–7. 15 indexed citations
5.
Yapanel, Umit, Dongxin Xu, John H. L. Hansen, et al.. (2009). Preliminary study of stress/neutral detection on recordings of children in the natural home environment. 1–5. 1 indexed citations
6.
Christakis, Dimitri, Jill Gilkerson, Jeffrey A. Richards, et al.. (2009). Audible Television and Decreased Adult Words, Infant Vocalizations, and Conversational Turns. Archives of Pediatrics and Adolescent Medicine. 163(6). 554–554. 236 indexed citations
7.
Xu, Dongxin, Jill Gilkerson, J Richards, Umit Yapanel, & Sharmistha Gray. (2009). Child vocalization composition as discriminant information for automatic autism detection. PubMed. 2009. 2518–2522. 33 indexed citations
8.
Warren, Steven F., Jill Gilkerson, Jeffrey A. Richards, et al.. (2009). What Automated Vocal Analysis Reveals About the Vocal Production and Language Learning Environment of Young Children with Autism. Journal of Autism and Developmental Disorders. 40(5). 555–569. 151 indexed citations
9.
Christakis, Dimitri, Jeffrey A. Richards, Frederick J. Zimmerman, et al.. (2009). A Population-Based Study. 1697 indexed citations breakdown →
10.
Yapanel, Umit & John H. L. Hansen. (2008). Towards an Intelligent Acoustic Front End for Automatic Speech Recognition: Built-in Speaker Normalization. EURASIP Journal on Audio Speech and Music Processing. 2008. 1–13. 1 indexed citations
11.
Yapanel, Umit & John H. L. Hansen. (2007). A new perceptually motivated MVDR-based acoustic front-end (PMVDR) for robust automatic speech recognition. Speech Communication. 50(2). 142–152. 68 indexed citations
12.
Yapanel, Umit & John H. L. Hansen. (2006). Towards an Intelligent Acoustic Front-End for Automatic Speech Recognition: Built-In Speaker Normalization (BISN). 1. 949–952. 2 indexed citations
13.
Yapanel, Umit & John H. L. Hansen. (2005). Acoustic modeling and speaker normalization strategies with application to robust in-vehicle speech recognition and dialect classification. Scandinavian Journal of Gastroenterology. 55(8). 920–923. 3 indexed citations
14.
Yapanel, Umit & John H. L. Hansen. (2003). A new perspective on feature extraction for robust in-vehicle speech recognition. 34 indexed citations
15.
Yapanel, Umit & S. Dharanipragada. (2003). Perceptual MVDR-based cepstral coefficients (PMCCs) for robust speech recognition. 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).. 1. I–644. 12 indexed citations
16.
Yapanel, Umit, Xianxian Zhang, & John Hansen. (2002). High performance digit recognition in real car environments. 793–796. 12 indexed citations
17.
Hansen, John H. L., Pongtep Angkititrakul, Stephen I. Gallant, et al.. (2001). CU-move": Analysis & corpus development for interactive in-vehicle speech systems. Conference of the International Speech Communication Association. 2023–2026. 21 indexed citations
18.
Hansen, John H. L., Pongtep Angkititrakul, Stephen I. Gallant, et al.. (2001). CU-move : analysis & corpus development for interactive in-vehicle speech systems. 2023–2026. 9 indexed citations
19.
Yapanel, Umit, John H. L. Hansen, Ruhi Sarikaya, & Bryan Pellom. (2001). Robust digit recognition in noise: an evaluation using the AURORA corpus. 209–212. 13 indexed citations
20.
Hansen, John H. L., Ruhi Sarikaya, Umit Yapanel, & Bryan Pellom. (2001). Robust speech recognition in noise: an evaluation using the SPINE corpus. 905–908. 18 indexed citations

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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