Mireia Díez
- Artificial Intelligence top 2%
- Signal Processing top 2%
- Experimental and Cognitive Psychology
- Computer Vision and Pattern Recognition
- Physiology
- Co-authors
- Lukáš BurgetAmparo VaronaMikel PeñagarikanoGermán BordelLuis Javier Rodríguez-FuentesJaň ČernockýPavel MatějkaFederico Landini
- Topics
- Speech Recognition and Synthesis (43 papers)Music and Audio Processing (30 papers)Speech and Audio Processing (24 papers)
In The Last Decade
Mireia Díez
49 papers receiving 514 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 544
- Signal Processing 453
- Experimental and Cognitive Psychology 32
- Computer Vision and Pattern Recognition 18
- Physiology 18
Countries citing papers authored by Mireia Díez
This map shows the geographic impact of Mireia Díez'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 Mireia Díez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mireia Díez more than expected).
Fields of papers citing papers by Mireia Díez
This network shows the impact of papers produced by Mireia Díez. 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 Mireia Díez. The network helps show where Mireia Díez may publish in the future.
Co-authorship network of co-authors of Mireia Díez
This figure shows the co-authorship network connecting the top 25 collaborators of Mireia Díez. A scholar is included among the top collaborators of Mireia Díez 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 Mireia Díez. Mireia Díez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 20 | |
| 6 | 8 | |
| 7 | 32 | |
| 8 | 74 | |
| 9 | GTTS-EHU Systems for QUESST at MediaEval 2014 | 7 |
| 10 | 58 | |
| 11 | GTTS Systems for the SWS Task at MediaEval 2013 | 15 |
| 12 | Language Recognition on Albayzin 2010 LRE using PLLR features | 2 |
| 13 | GTTS System for the Spoken Web Search Task at MediaEval 2012. | 5 |
| 14 | KALAKA-2: a TV Broadcast Speech Database for the Recognition of Iberian Languages in Clean and Noisy Environments | 5 |
| 15 | Evaluation of spoken language recognition technology using broadcast speech: performance and challenges. | 3 |
| 16 | A spoken document retrieval system for TV broadcast news in Spanish and Basque | 1 |
| 17 | 4 | |
| 18 | Verification of the four Spanish official languages on TV show recordings | 1 |
| 19 | KALAKA: A TV Broadcast Speech Database for the Evaluation of Language Recognition Systems. | 9 |
| 20 | 1 |
About Mireia Díez
Mireia Díez is a scholar working on Signal Processing, Artificial Intelligence and Language and Linguistics, having authored 53 papers that have together received 569 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (43 papers), Music and Audio Processing (30 papers) and Speech and Audio Processing (24 papers). The work is most often cited by research in Signal Processing (453 citations), Artificial Intelligence (544 citations) and Experimental and Cognitive Psychology (32 citations). Mireia Díez has collaborated with scholars based in Spain, Czechia and Japan. Frequent co-authors include Lukáš Burget, Amparo Varona, Mikel Peñagarikano, Germán Bordel, Luis Javier Rodríguez-Fuentes, Jaň Černocký, Pavel Matějka, Federico Landini, Oldřich Plchot and Ondřej Novotný. Their work appears in journals such as European Radiology, IEEE Signal Processing Letters and Language Resources and Evaluation.
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.