Karolina Smeds

804 total citations
27 papers, 582 citations indexed

About

Karolina Smeds is a scholar working on Cognitive Neuroscience, Speech and Hearing and Signal Processing. According to data from OpenAlex, Karolina Smeds has authored 27 papers receiving a total of 582 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cognitive Neuroscience, 19 papers in Speech and Hearing and 10 papers in Signal Processing. Recurrent topics in Karolina Smeds's work include Hearing Loss and Rehabilitation (23 papers), Noise Effects and Management (19 papers) and Speech and Audio Processing (10 papers). Karolina Smeds is often cited by papers focused on Hearing Loss and Rehabilitation (23 papers), Noise Effects and Management (19 papers) and Speech and Audio Processing (10 papers). Karolina Smeds collaborates with scholars based in Sweden, Australia and United Kingdom. Karolina Smeds's co-authors include Florian Wolters, Arne Leijon, Gitte Keidser, Graham Naylor, Inga Holube, Erik M. Schmidt, Mark G. Carpenter, Stefan Launer, Douglas S. Brungart and Volker Hohmann and has published in prestigious journals such as The Journal of the Acoustical Society of America, Ear and Hearing and International Journal of Audiology.

In The Last Decade

Karolina Smeds

25 papers receiving 547 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Karolina Smeds Sweden 10 533 420 205 125 54 27 582
Elizabeth Stangl United States 13 556 1.0× 461 1.1× 163 0.8× 145 1.2× 64 1.2× 24 597
Tobias Neher Denmark 16 728 1.4× 571 1.4× 247 1.2× 287 2.3× 102 1.9× 70 772
Sébastien Santurette Denmark 16 534 1.0× 309 0.7× 185 0.9× 164 1.3× 67 1.2× 44 595
Mary T. Cord United States 15 727 1.4× 507 1.2× 318 1.6× 252 2.0× 82 1.5× 32 773
Daniel Valente United States 11 354 0.7× 239 0.6× 79 0.4× 94 0.8× 82 1.5× 24 487
Sridhar Kalluri United States 15 873 1.6× 597 1.4× 246 1.2× 306 2.4× 146 2.7× 35 916
Elizabeth Convery Australia 17 589 1.1× 416 1.0× 169 0.8× 155 1.2× 22 0.4× 32 660
Sabine Hochmuth Germany 11 600 1.1× 343 0.8× 318 1.6× 207 1.7× 104 1.9× 20 666
Joshua M. Alexander United States 14 525 1.0× 254 0.6× 310 1.5× 186 1.5× 101 1.9× 46 610
Rauna K. Surr United States 13 745 1.4× 499 1.2× 289 1.4× 309 2.5× 50 0.9× 29 787

Countries citing papers authored by Karolina Smeds

Since Specialization
Citations

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

Fields of papers citing papers by Karolina Smeds

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Karolina Smeds

This figure shows the co-authorship network connecting the top 25 collaborators of Karolina Smeds. A scholar is included among the top collaborators of Karolina Smeds 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 Karolina Smeds. Karolina Smeds 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.
Hadley, Lauren V., et al.. (2025). Effective Design for Experiments on Small-Group Conversation: Insights From an Example Study. American Journal of Audiology. 34(2). 305–320.
2.
Holube, Inga, Lorienne M. Jenstad, Dina Lelic, et al.. (2024). Implementing Ecological Momentary Assessment in Audiological Research: Opportunities and Challenges. American Journal of Audiology. 33(3). 648–673. 5 indexed citations
3.
Akeroyd, Michael A., Louise Hickson, Inga Holube, et al.. (2024). Evaluating the ecological validity of spatial hearing. 411–414. 1 indexed citations
4.
Lelic, Dina, et al.. (2023). Focusing on positive listening experiences improves hearing aid outcomes in experienced hearing aid users. International Journal of Audiology. 63(6). 420–430. 10 indexed citations
5.
Leijon, Arne, et al.. (2023). Bayesian analysis of Ecological Momentary Assessment (EMA) data collected in adults before and after hearing rehabilitation. Frontiers in Digital Health. 5. 1100705–1100705. 3 indexed citations
6.
Smeds, Karolina, et al.. (2023). Test-retest reliability of the urban outdoor situated phoneme (SiP) test*. International Journal of Audiology. 63(11). 859–866.
7.
Keidser, Gitte, Graham Naylor, Douglas S. Brungart, et al.. (2022). Comment on the Point of View “Ecological Validity, External Validity and Mundane Realism in Hearing Science”. Ear and Hearing. 43(5). 1601–1602. 3 indexed citations
8.
Gotowiec, Sarah, et al.. (2022). Conversation success in one-to-one and group conversation: a group concept mapping study of adults with normal and impaired hearing. International Journal of Audiology. 62(9). 868–876. 8 indexed citations
9.
Gotowiec, Sarah, et al.. (2021). Understanding patient empowerment along the hearing health journey. International Journal of Audiology. 61(2). 148–158. 17 indexed citations
10.
Smeds, Karolina, et al.. (2018). Ecological momentary assessments for evaluation of hearing-aid preference. The Journal of the Acoustical Society of America. 143(3_Supplement). 1742–1742. 5 indexed citations
11.
Wolters, Florian, et al.. (2016). Common Sound Scenarios: A Context-Driven Categorization of Everyday Sound Environments for Application in Hearing-Device Research. Journal of the American Academy of Audiology. 27(7). 527–540. 41 indexed citations
12.
Wolters, Florian, et al.. (2015). Predicting individual hearing-aid preference in the field using laboratory paired comparisons. 5. 261–268. 1 indexed citations
13.
Smeds, Karolina, et al.. (2015). Estimation of Signal-to-Noise Ratios in Realistic Sound Scenarios. Journal of the American Academy of Audiology. 26(2). 183–196. 225 indexed citations
14.
Smeds, Karolina, et al.. (2014). Comparison of predictive measures of speech recognition after noise reduction processing. The Journal of the Acoustical Society of America. 136(3). 1363–1374. 7 indexed citations
15.
Smeds, Karolina, et al.. (2010). Objective Measures to Quantify the Perceptual Effects of Noise Reduction in Hearing Aids. 101–108. 3 indexed citations
16.
Smeds, Karolina, et al.. (2009). Noise reduction in modern hearing aids – long-term average gain measurements using speech. 2. 445–452. 4 indexed citations
17.
Smeds, Karolina, Gitte Keidser, Harvey Dillon, et al.. (2005). Preferred overall loudness. I: Sound field presentation in the laboratory. International Journal of Audiology. 45(1). 2–11. 20 indexed citations
18.
Smeds, Karolina, Gitte Keidser, Harvey Dillon, et al.. (2005). Preferred overall loudness. II: Listening through hearing aids in field and laboratory tests. International Journal of Audiology. 45(1). 12–25. 38 indexed citations
19.
Smeds, Karolina. (2004). Is Normal or Less Than Normal Overall Loudness Preferred by First-Time Hearing Aid Users?. Ear and Hearing. 25(2). 159–172. 34 indexed citations
20.
Smeds, Karolina & Arne Leijon. (2001). Threshold-based fitting methods for non-linear (WDRC) hearing instruments - comparison of acoustic characteristics. Scandinavian Audiology. 30(4). 213–222. 7 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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