Diego Castán
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition
- Physiology
- Experimental and Cognitive Psychology
- Co-authors
- Mitchell McLarenLuciana FerrerAaron LawsonMahesh Kumar NandwanaEduardo LleidaAlfonso OrtegaAntonio MiguelEmre Yılmaz
- Topics
- Speech Recognition and Synthesis (26 papers)Speech and Audio Processing (20 papers)Music and Audio Processing (19 papers)
- Journals
- IEEE/ACM Transactions on Audio Speech and Language ProcessingEURASIP Journal on Audio Speech and Music ProcessingNational University of Singapore
- Partner nations
- SpainUnited StatesArgentina
In The Last Decade
Diego Castán
30 papers receiving 296 citations
Peers
Comparison fields: 5 of 23
- Artificial Intelligence 305
- Signal Processing 292
- Computer Vision and Pattern Recognition 50
- Physiology 5
- Experimental and Cognitive Psychology 4
Countries citing papers authored by Diego Castán
This map shows the geographic impact of Diego Castán'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 Diego Castán with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Castán more than expected).
Fields of papers citing papers by Diego Castán
This network shows the impact of papers produced by Diego Castán. 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 Diego Castán. The network helps show where Diego Castán may publish in the future.
Co-authorship network of co-authors of Diego Castán
This figure shows the co-authorship network connecting the top 25 collaborators of Diego Castán. A scholar is included among the top collaborators of Diego Castán 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 Diego Castán. Diego Castán is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | Tampered Speaker Inconsistency Detection with Phonetically Aware Audio-visual Features | 9 |
| 5 | 9 | |
| 6 | 4 | |
| 7 | 6 | |
| 8 | 3 | |
| 9 | 2 | |
| 10 | 149 | |
| 11 | 7 | |
| 12 | 8 | |
| 13 | 15 | |
| 14 | ViVoLab and CVLab - MediaEval 2014: Violent Scenes Detection Affect Task | 6 |
| 15 | 1 | |
| 16 | Broadcast News Segmentation with Factor Analysis System. | 3 |
| 17 | Segmental-GMM Approach based on Acoustic Concept Segmentation | 1 |
| 18 | 4 | |
| 19 | 3 | |
| 20 | 6 |
About Diego Castán
Diego Castán is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 30 papers that have together received 343 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (26 papers), Speech and Audio Processing (20 papers) and Music and Audio Processing (19 papers). The work is most often cited by research in Signal Processing (292 citations), Artificial Intelligence (305 citations) and Computer Vision and Pattern Recognition (50 citations). Diego Castán has collaborated with scholars based in Spain, United States and Argentina. Frequent co-authors include Mitchell McLaren, Luciana Ferrer, Aaron Lawson, Mahesh Kumar Nandwana, Eduardo Lleida, Alfonso Ortega, Antonio Miguel, Emre Yılmaz, Martin Graciarena and Jesús Villalba. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, EURASIP Journal on Audio Speech and Music Processing and National University of Singapore.
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.