Daniel Garcia-Romero
- Artificial Intelligence top 0.1%
- Signal Processing top 0.05%
- Computer Vision and Pattern Recognition top 2%
- Experimental and Cognitive Psychology top 5%
- Physiology
- Co-authors
- David SnyderDaniel PoveySanjeev KhudanpurGregory SellCarol Espy-WilsonAlan McCreeXinhui ZhouJavier Ortega-García
- Topics
- Speech Recognition and Synthesis (61 papers)Speech and Audio Processing (57 papers)Music and Audio Processing (47 papers)
- Journals
- The Journal of the Acoustical Society of AmericaPattern RecognitionPattern Recognition Letters
- Partner nations
- United StatesSpainUnited Kingdom
In The Last Decade
Daniel Garcia-Romero
67 papers receiving 4.5k citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 4.5k
- Signal Processing 4.1k
- Computer Vision and Pattern Recognition 425
- Experimental and Cognitive Psychology 187
- Physiology 156
Countries citing papers authored by Daniel Garcia-Romero
This map shows the geographic impact of Daniel Garcia-Romero'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 Daniel Garcia-Romero with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Garcia-Romero more than expected).
Fields of papers citing papers by Daniel Garcia-Romero
This network shows the impact of papers produced by Daniel Garcia-Romero. 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 Daniel Garcia-Romero. The network helps show where Daniel Garcia-Romero may publish in the future.
Co-authorship network of co-authors of Daniel Garcia-Romero
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Garcia-Romero. A scholar is included among the top collaborators of Daniel Garcia-Romero 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 Daniel Garcia-Romero. Daniel Garcia-Romero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 10 | |
| 4 | 0 | |
| 5 | 149 | |
| 6 | 23 | |
| 7 | 50 | |
| 8 | 121 | |
| 9 | 115 | |
| 10 | Deep Neural Network Embeddings for Text-Independent Speaker Verificationbreakdown → | 454 |
| 11 | 9 | |
| 12 | 6 | |
| 13 | 91 | |
| 14 | 1 | |
| 15 | 4 | |
| 16 | Analysis of i-vector length normalization in speaker recognition systemsbreakdown → | 675 |
| 17 | 105 | |
| 18 | 12 | |
| 19 | Joint Factor Analysis for Speaker Recognition reinterpreted as Signal Coding using Overcomplete Dictionaries | 14 |
| 20 | On the use of quality measures for text-independent speaker recognition. | 16 |
About Daniel Garcia-Romero
Daniel Garcia-Romero is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 71 papers that have together received 5.0k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (61 papers), Speech and Audio Processing (57 papers) and Music and Audio Processing (47 papers). The work is most often cited by research in Signal Processing (4.1k citations), Artificial Intelligence (4.5k citations) and Computer Vision and Pattern Recognition (425 citations). Daniel Garcia-Romero has collaborated with scholars based in United States, Spain and United Kingdom. Frequent co-authors include David Snyder, Daniel Povey, Sanjeev Khudanpur, Gregory Sell, Carol Espy-Wilson, Alan McCree, Xinhui Zhou, Javier Ortega-García, Joaquín González-Rodríguez and Julián Fiérrez. Their work appears in journals such as The Journal of the Acoustical Society of America, Pattern Recognition and Pattern Recognition Letters.
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.