Sebastian Möller

Artificial Intelligence · 2013–2021

A researcher in the Science corpus: 10 papers; trusts 25 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it; #20,488 of 35,345 by trust here, #25,040 by citations
• Evaluation & Benchmarks — 25 citations into it
• Natural Language Processing — 20 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it; #10,562 of 21,575 by trust here, #20,756 by citations
• Signal Processing — 11 citations into it; #3,046 of 7,572 by trust here, #4,900 by citations
• Computer Science Applications — 10 citations into it

Whom Sebastian Möller trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Simon King
2. Babak Naderi
3. Chin-Yew Lin
4. Hoa Trang Dang
5. Gy Zou
6. Ani Nenkova
7. Chen-Chou Lo

Who trusts Sebastian Möller overall

1. Babak Naderi
2. Ross Cutler
3. Zi-Hua Zhang
4. Junyi Ao

Papers from Sebastian Möller's perspective

Ordered by how strongly the researchers Sebastian Möller trusts endorse each paper. Same corpus, a different order for every researcher.

1. Bleu: a Method for Automatic Evaluation of Machine Translation
2. Attention is All you Need (Neural Information Processing Systems)
3. Long Short-Term Memory
4. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet classification with deep convolutional neural networks
9. ROUGE: A Package for Automatic Evaluation of Summaries
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Deep Learning Based Assessment of Synthetic Speech Naturalness (2020) — 85 citations
• Effect of trapping questions on the reliability of speech quality judgments in a crowdsourcing paradigm (2015) — 40 citations
• Robustness in speech quality assessment and temporal training expiry in mobile crowdsourcing environments (2015) — 17 citations
• NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets (2021) — 509 citations
• Best Practices for Crowd-based Evaluation of German Summarization: Comparing Crowd, Expert and Automatic Evaluation (2020) — 18 citations
• Transformation of Mean Opinion Scores to Avoid Misleading of Ranked Based Statistical Techniques (2020) — 18 citations
• Impact of the Number of Votes on the Reliability and Validity of Subjective Speech Quality Assessment in the Crowdsourcing Approach (2020) — 13 citations
• Application of Just-Noticeable Difference in Quality as Environment Suitability Test for Crowdsourcing Speech Quality Assessment Task (2020) — 20 citations
• Effect of being observed on the reliability of responses in crowdsourcing micro-task platforms (2015) — 21 citations
• Qualinet White Paper on Definitions of Quality of Experience (2013) — 923 citations