Sandra Ottl

860 total citations
20 papers, 483 citations indexed

About

Sandra Ottl is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sandra Ottl has authored 20 papers receiving a total of 483 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Signal Processing, 6 papers in Artificial Intelligence and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sandra Ottl's work include Music and Audio Processing (11 papers), Speech and Audio Processing (7 papers) and Emotion and Mood Recognition (5 papers). Sandra Ottl is often cited by papers focused on Music and Audio Processing (11 papers), Speech and Audio Processing (7 papers) and Emotion and Mood Recognition (5 papers). Sandra Ottl collaborates with scholars based in Germany and United Kingdom. Sandra Ottl's co-authors include Björn W. Schuller, Shahin Amiriparian, Maurice Gerczuk, Nicholas Cummins, Alice Baird, Sergey Pugachevskiy, Michael Freitag, Lukas Stappen, Maximilian Schmitt and Andreas Triantafyllopoulos and has published in prestigious journals such as IEEE Transactions on Affective Computing, iScience and Frontiers in Artificial Intelligence.

In The Last Decade

Sandra Ottl

20 papers receiving 459 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sandra Ottl Germany 13 207 192 191 77 74 20 483
Maurice Gerczuk Germany 14 260 1.3× 259 1.3× 246 1.3× 101 1.3× 92 1.2× 40 641
Andreas Tsiartas United States 13 280 1.4× 297 1.5× 154 0.8× 67 0.9× 40 0.5× 35 632
Sergey Pugachevskiy Germany 7 170 0.8× 129 0.7× 103 0.5× 43 0.6× 56 0.8× 7 320
Theodoros Iliou Greece 11 235 1.1× 185 1.0× 344 1.8× 75 1.0× 91 1.2× 20 591
Simone Hantke Germany 15 249 1.2× 253 1.3× 167 0.9× 66 0.9× 70 0.9× 32 553
Elizabeth Godoy United States 9 208 1.0× 217 1.1× 211 1.1× 91 1.2× 43 0.6× 20 429
Zhongtian Bao China 7 193 0.9× 178 0.9× 315 1.6× 53 0.7× 61 0.8× 7 481
Zhaocheng Huang Australia 13 109 0.5× 162 0.8× 293 1.5× 122 1.6× 41 0.6× 23 403
Jérôme Urbain Belgium 13 111 0.5× 118 0.6× 174 0.9× 120 1.6× 62 0.8× 26 456
Lukas Stappen Germany 12 117 0.6× 261 1.4× 249 1.3× 118 1.5× 73 1.0× 25 516

Countries citing papers authored by Sandra Ottl

Since Specialization
Citations

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

Fields of papers citing papers by Sandra Ottl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sandra Ottl

This figure shows the co-authorship network connecting the top 25 collaborators of Sandra Ottl. A scholar is included among the top collaborators of Sandra Ottl 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 Sandra Ottl. Sandra Ottl 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.
Bergler, Christian, Maurice Gerczuk, Chloë Brown, et al.. (2023). A summary of the ComParE COVID-19 challenges. Frontiers in Digital Health. 5. 1058163–1058163. 7 indexed citations
2.
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
3.
Amiriparian, Shahin, et al.. (2022). DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing From Decentralized Data. Frontiers in Artificial Intelligence. 5. 856232–856232. 21 indexed citations
4.
Amiriparian, Shahin, Andreas Triantafyllopoulos, Maurice Gerczuk, et al.. (2022). Towards Heart Rate Categorisation from Speech in Outdoor Running Conditions. 1–5. 1 indexed citations
5.
Triantafyllopoulos, Andreas, Shahin Amiriparian, Sandra Ottl, et al.. (2022). Investigating Individual- and Group-Level Model Adaptation for Self-Reported Runner Exertion Prediction from Biomechanics. 1–4. 3 indexed citations
6.
Triantafyllopoulos, Andreas, Sandra Ottl, Patrick Schneeweiß, et al.. (2022). Fatigue Prediction in Outdoor Running Conditions using Audio Data. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2022. 2623–2626. 4 indexed citations
7.
Triantafyllopoulos, Andreas, Shahin Amiriparian, Sandra Ottl, et al.. (2022). Improving Exertion and Wellbeing Prediction in Outdoor Running Conditions using Audio-based Surface Recognition. 19–27. 2 indexed citations
8.
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
9.
Baird, Alice, Andreas Triantafyllopoulos, Sandra Zänkert, et al.. (2021). An Evaluation of Speech-Based Recognition of Emotional and Physiological Markers of Stress. Frontiers in Computer Science. 3. 23 indexed citations
10.
Amiriparian, Shahin, Maurice Gerczuk, Sandra Ottl, et al.. (2020). Towards cross-modal pre-training and learning tempo-spatial characteristics for audio recognition with convolutional and recurrent neural networks. EURASIP Journal on Audio Speech and Music Processing. 2020(1). 15 indexed citations
11.
Amiriparian, Shahin, et al.. (2020). Unsupervised Representation Learning with Attention and Sequence to Sequence Autoencoders to Predict Sleepiness From Speech. OPUS (Augsburg University). 11–17. 2 indexed citations
12.
Ottl, Sandra, et al.. (2020). Group-level Speech Emotion Recognition Utilising Deep Spectrum Features. OPUS (Augsburg University). 821–826. 15 indexed citations
13.
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
14.
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
15.
Amiriparian, Shahin, Maurice Gerczuk, Lukas Stappen, et al.. (2019). Audio-based Recognition of Bipolar Disorder Utilising Capsule Networks. OPUS (Augsburg University). 1–7. 14 indexed citations
16.
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
17.
Amiriparian, Shahin, Alice Baird, Alyssa M. Alcorn, et al.. (2018). Recognition of Echolalic Autistic Child Vocalisations Utilising Convolutional Recurrent Neural Networks. OPUS (Augsburg University). 2334–2338. 12 indexed citations
18.
Cummins, Nicholas, Shahin Amiriparian, Sandra Ottl, et al.. (2018). Multimodal Bag-of-Words for Cross Domains Sentiment Analysis. OPUS (Augsburg University). 4954–4958. 27 indexed citations
19.
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
20.
Amiriparian, Shahin, Nicholas Cummins, Sandra Ottl, Maurice Gerczuk, & Björn W. Schuller. (2017). Sentiment analysis using image-based deep spectrum features. OPUS (Augsburg University). 26–29. 27 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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