Javier Gónzalez-Domínguez

21 papers receiving 1.1k citations

Hit Papers

Deep neural networks for small footprint text-dependent s...20142026201820222014200400600

Peers

Javier Gónzalez-Domínguez
Comparison fields: 5 of 76
  • Artificial Intelligence 1.1k
  • Signal Processing 932
  • Computer Vision and Pattern Recognition 95
  • Experimental and Cognitive Psychology 34
  • Electrical and Electronic Engineering 26
Replace Hank Liao with:
Hank Liao United States
Owen Kimball United States
Yossi Adi Israel
Yeshwant K. Muthusamy United States
Niko Brümmer Czechia
Ondřej Glembek Czechia
Hirofumi Inaguma Japan
Elliot Singer United States
Sachin Kajarekar United States
Changhan Wang United States
Javier Gónzalez-Domínguez relative to Hank Liao United States Hank Liao's profile →
Citations per field
00.5×1.5×2.2×
Hank Liao · 1×
Citations per year

Countries citing papers authored by Javier Gónzalez-Domínguez

Since Specialization
Citations

This map shows the geographic impact of Javier Gónzalez-Domínguez'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 Javier Gónzalez-Domínguez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Javier Gónzalez-Domínguez more than expected).

Fields of papers citing papers by Javier Gónzalez-Domínguez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Javier Gónzalez-Domínguez. 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 Javier Gónzalez-Domínguez. The network helps show where Javier Gónzalez-Domínguez may publish in the future.

Co-authorship network of co-authors of Javier Gónzalez-Domínguez

This figure shows the co-authorship network connecting the top 25 collaborators of Javier Gónzalez-Domínguez. A scholar is included among the top collaborators of Javier Gónzalez-Domínguez 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 Javier Gónzalez-Domínguez. Javier Gónzalez-Domínguez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 106
2 44
3 30
4
Deep neural networks for small footprint text-dependent speaker verificationbreakdown →
645
5 42
6 47
7 140
8 29
9 86
10 14
11 7
12 2
13
On the Use of Factor Analysis with Restricted Target Data in Speaker Verification
4
14 7
15 2
16
ATVS-UAM NIST SRE 2010 System Description
1
17 1
18 11
19 2
20 5

About Javier Gónzalez-Domínguez

Javier Gónzalez-Domínguez is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 1.2k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (19 papers), Speech and Audio Processing (15 papers) and Music and Audio Processing (15 papers). The work is most often cited by research in Signal Processing (932 citations), Artificial Intelligence (1.1k citations) and Computer Vision and Pattern Recognition (95 citations). Javier Gónzalez-Domínguez has collaborated with scholars based in Spain, United States and Australia. Frequent co-authors include Ignacio López Moreno, Ehsan Variani, Xin Lei, Erik McDermott, Joaquín González-Rodríguez, Pedro J. Moreno, David Martínez, Oldřich Plchot, Doroteo T. Toledano and Alicia Lozano-Díez. Their work appears in journals such as PLoS ONE, The Journal of the Acoustical Society of America and Neural Networks.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026