Maurice Gerczuk

1.1k total citations
40 papers, 641 citations indexed

About

Maurice Gerczuk is a scholar working on Experimental and Cognitive Psychology, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Maurice Gerczuk has authored 40 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Experimental and Cognitive Psychology, 16 papers in Signal Processing and 11 papers in Artificial Intelligence. Recurrent topics in Maurice Gerczuk's work include Music and Audio Processing (15 papers), Emotion and Mood Recognition (13 papers) and Speech and Audio Processing (9 papers). Maurice Gerczuk is often cited by papers focused on Music and Audio Processing (15 papers), Emotion and Mood Recognition (13 papers) and Speech and Audio Processing (9 papers). Maurice Gerczuk collaborates with scholars based in Germany, United Kingdom and France. Maurice Gerczuk's co-authors include Björn W. Schuller, Shahin Amiriparian, Sandra Ottl, Nicholas Cummins, Sergey Pugachevskiy, Alice Baird, Michael Freitag, Anton Batliner, Andreas Triantafyllopoulos and Maximilian Schmitt and has published in prestigious journals such as Behaviour Research and Therapy, Depression and Anxiety and IEEE Transactions on Affective Computing.

In The Last Decade

Maurice Gerczuk

39 papers receiving 617 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maurice Gerczuk Germany 14 260 259 246 101 92 40 641
Sandra Ottl Germany 13 207 0.8× 192 0.7× 191 0.8× 77 0.8× 74 0.8× 20 483
Andreas Tsiartas United States 13 280 1.1× 297 1.1× 154 0.6× 67 0.7× 40 0.4× 35 632
Simone Hantke Germany 15 249 1.0× 253 1.0× 167 0.7× 66 0.7× 70 0.8× 32 553
Shahin Amiriparian Germany 21 524 2.0× 498 1.9× 464 1.9× 177 1.8× 189 2.1× 73 1.2k
Theodoros Iliou Greece 11 235 0.9× 185 0.7× 344 1.4× 75 0.7× 91 1.0× 20 591
Gilles Degottex Greece 11 385 1.5× 501 1.9× 270 1.1× 75 0.7× 111 1.2× 28 744
Elliot Moore United States 14 162 0.6× 235 0.9× 297 1.2× 93 0.9× 65 0.7× 42 624
Zhaocheng Huang Australia 13 109 0.4× 162 0.6× 293 1.2× 122 1.2× 41 0.4× 23 403
Colleen Richey United States 16 270 1.0× 511 2.0× 198 0.8× 90 0.9× 50 0.5× 35 797
Elizabeth Godoy United States 9 208 0.8× 217 0.8× 211 0.9× 91 0.9× 43 0.5× 20 429

Countries citing papers authored by Maurice Gerczuk

Since Specialization
Citations

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

Fields of papers citing papers by Maurice Gerczuk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maurice Gerczuk

This figure shows the co-authorship network connecting the top 25 collaborators of Maurice Gerczuk. A scholar is included among the top collaborators of Maurice Gerczuk 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 Maurice Gerczuk. Maurice Gerczuk 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.
Gerczuk, Maurice, Shahin Amiriparian, David Daniel Ebert, et al.. (2024). Validation of Machine Learning-Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care. Depression and Anxiety. 2024. 1–12. 5 indexed citations
2.
Amiriparian, Shahin, Maurice Gerczuk, Lukas Stappen, et al.. (2024). The MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor Recognition. 1–9. 10 indexed citations
3.
Gerczuk, Maurice, et al.. (2024). Prosody-focused feedback enhances the efficacy of anti-depressive self-statements in depressed individuals – A randomized controlled trial. Behaviour Research and Therapy. 184. 104667–104667. 1 indexed citations
4.
Amiriparian, Shahin, et al.. (2023). Personalised Speech-Based Heart Rate Categorisation Using Weighted-Instance Learning. 9–13. 1 indexed citations
5.
Gerczuk, Maurice, Anton Batliner, Christian Bergler, et al.. (2023). Classification of stuttering – The ComParE challenge and beyond. Computer Speech & Language. 81. 101519–101519. 6 indexed citations
6.
Schuller, Björn W., Anton Batliner, Shahin Amiriparian, et al.. (2023). The ACM Multimedia 2023 Computational Paralinguistics Challenge: Emotion Share & Requests. OPUS (Augsburg University). 9635–9639. 11 indexed citations
7.
8.
Gerczuk, Maurice, Anton Batliner, Christian Bergler, et al.. (2023). Classification of Stuttering – the Compare Challenge and Beyond. SSRN Electronic Journal. 2 indexed citations
9.
Schuller, Björn W., et al.. (2023). Computational charisma—A brick by brick blueprint for building charismatic artificial intelligence. Frontiers in Computer Science. 5. 3 indexed citations
10.
Harrer, Mathias, Andreas Triantafyllopoulos, Maurice Gerczuk, et al.. (2022). Personalised depression forecasting using mobile sensor data and ecological momentary assessment. Frontiers in Digital Health. 4. 964582–964582. 27 indexed citations
11.
Gerczuk, Maurice, et al.. (2022). Personalised Deep Learning for Monitoring Depressed Mood from Speech. 1–5. 4 indexed citations
12.
Triantafyllopoulos, Andreas, Anton Batliner, Maurice Gerczuk, et al.. (2022). Distinguishing between pre- and post-treatment in the speech of patients with chronic obstructive pulmonary disease. Interspeech 2022. 3623–3627. 5 indexed citations
13.
Ottl, Sandra, Shahin Amiriparian, Maurice Gerczuk, & Björn W. Schuller. (2022). motilitAI: A machine learning framework for automatic prediction of human sperm motility. iScience. 25(8). 104644–104644. 27 indexed citations
14.
Gerczuk, Maurice, Shahin Amiriparian, Sandra Ottl, & Björn W. Schuller. (2021). EmoNet: A Transfer Learning Framework for Multi-Corpus Speech Emotion Recognition. IEEE Transactions on Affective Computing. 14(2). 1472–1487. 39 indexed citations
15.
Amiriparian, Shahin, Nicholas Cummins, Maurice Gerczuk, et al.. (2019). “Are You Playing a Shooter Again?!” Deep Representation Learning for Audio-Based Video Game Genre Recognition. IEEE Transactions on Games. 12(2). 145–154. 13 indexed citations
16.
Amiriparian, Shahin, Maurice Gerczuk, Eduardo Coutinho, et al.. (2019). Emotion and themes recognition in music utilising convolutional and recurrent neural networks. OPUS (Augsburg University). 4 indexed citations
17.
Amiriparian, Shahin, Maurice Gerczuk, Sandra Ottl, et al.. (2018). Bag-of-Deep-Features: Noise-Robust Deep Feature Representations for Audio Analysis. OPUS (Augsburg University). 1–7. 21 indexed citations
18.
Freitag, Michael, et al.. (2018). A Fusion of Deep Convolutional Generative Adversarial Networks and Sequence to Sequence Autoencoders for Acoustic Scene Classification. OPUS (Augsburg University). 977–981. 11 indexed citations
19.
Freitag, Michael, Shahin Amiriparian, Nicholas Cummins, Maurice Gerczuk, & Björn W. Schuller. (2017). An ‘End-to-Evolution’ Hybrid Approach for Snore Sound Classification. OPUS (Augsburg University). 3507–3511. 27 indexed citations
20.
Amiriparian, Shahin, Maurice Gerczuk, Sandra Ottl, et al.. (2017). Snore Sound Classification Using Image-Based Deep Spectrum Features. OPUS (Augsburg University). 3512–3516. 206 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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