Christian Plahl
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 10%
- Human-Computer Interaction top 10%
- Biomedical Engineering
- Co-authors
- Hermann NeyRalf SchlüterFabio ValenteStefan HahnGeorg HeigoldPhilippe DreuwPatrick DoetschBjörn Hoffmeister
- Topics
- Speech and Audio Processing (15 papers)Speech Recognition and Synthesis (15 papers)Music and Audio Processing (9 papers)
- Journals
- IEEE Transactions on Audio Speech and Language ProcessingIEEE Transactions on Consumer ElectronicsInfoscience (Ecole Polytechnique Fédérale de Lausanne)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Christian Plahl
21 papers receiving 323 citations
Peers
Comparison fields: 5 of 38
- Artificial Intelligence 300
- Signal Processing 212
- Computer Vision and Pattern Recognition 107
- Human-Computer Interaction 35
- Biomedical Engineering 24
Countries citing papers authored by Christian Plahl
This map shows the geographic impact of Christian Plahl'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 Christian Plahl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christian Plahl more than expected).
Fields of papers citing papers by Christian Plahl
This network shows the impact of papers produced by Christian Plahl. 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 Christian Plahl. The network helps show where Christian Plahl may publish in the future.
Co-authorship network of co-authors of Christian Plahl
This figure shows the co-authorship network connecting the top 25 collaborators of Christian Plahl. A scholar is included among the top collaborators of Christian Plahl 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 Christian Plahl. Christian Plahl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | Neural network based feature extraction for speech and image recognition | 1 |
| 3 | 13 | |
| 4 | 28 | |
| 5 | 19 | |
| 6 | 36 | |
| 7 | 4 | |
| 8 | 8 | |
| 9 | 36 | |
| 10 | 27 | |
| 11 | 2 | |
| 12 | 16 | |
| 13 | 30 | |
| 14 | 14 | |
| 15 | 14 | |
| 16 | Log-Linear Framework for Linear Feature Transformations in Speech Recognition | 5 |
| 17 | 17 | |
| 18 | 20 | |
| 19 | 38 | |
| 20 | 16 |
About Christian Plahl
Christian Plahl is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 372 indexed citations. Recurring topics across this work include Speech and Audio Processing (15 papers), Speech Recognition and Synthesis (15 papers) and Music and Audio Processing (9 papers). The work is most often cited by research in Signal Processing (212 citations), Artificial Intelligence (300 citations) and Human-Computer Interaction (35 citations). Christian Plahl has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Hermann Ney, Ralf Schlüter, Fabio Valente, Stefan Hahn, Georg Heigold, Philippe Dreuw, Patrick Doetsch, Björn Hoffmeister, Christian Gollan and Mathew Magimai.-Doss. Their work appears in journals such as IEEE Transactions on Audio Speech and Language Processing, IEEE Transactions on Consumer Electronics and Infoscience (Ecole Polytechnique Fédérale de Lausanne).
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.