Esteban Maestre

605 total citations
55 papers, 299 citations indexed

About

Esteban Maestre is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Cognitive Neuroscience. According to data from OpenAlex, Esteban Maestre has authored 55 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Computer Vision and Pattern Recognition, 49 papers in Signal Processing and 28 papers in Cognitive Neuroscience. Recurrent topics in Esteban Maestre's work include Music Technology and Sound Studies (51 papers), Music and Audio Processing (47 papers) and Neuroscience and Music Perception (24 papers). Esteban Maestre is often cited by papers focused on Music Technology and Sound Studies (51 papers), Music and Audio Processing (47 papers) and Neuroscience and Music Perception (24 papers). Esteban Maestre collaborates with scholars based in Spain, Canada and United States. Esteban Maestre's co-authors include Rafael Ramírez, Alfonso Pérez, Xavier Serra, Jordi Bonada, Merlijn Blaauw, Gary Scavone, Julius O. Smith, Emília Gómez, Óscar Mayor and Antonio Pertusa and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of the Acoustical Society of America and Frontiers in Psychology.

In The Last Decade

Esteban Maestre

53 papers receiving 272 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Esteban Maestre Spain	11	242	227	159	25	22	55	299
Alfonso Pérez Spain	11	174 0.7×	164 0.7×	124 0.8×	31 1.2×	14 0.6×	38	246
Ross Kirk United Kingdom	7	229 0.9×	111 0.5×	171 1.1×	21 0.8×	20 0.9×	19	287
Óscar Mayor Spain	8	259 1.1×	324 1.4×	132 0.8×	46 1.8×	13 0.6×	19	401
Jordi Janer Spain	10	177 0.7×	275 1.2×	99 0.6×	13 0.5×	7 0.3×	43	333
Arne Eigenfeldt Canada	11	217 0.9×	172 0.8×	121 0.8×	13 0.5×	11 0.5×	43	269
Diemo Schwarz France	8	172 0.7×	172 0.8×	88 0.6×	13 0.5×	18 0.8×	25	242
Raymond Migneco United States	6	158 0.7×	248 1.1×	118 0.7×	15 0.6×	20 0.9×	13	318
Christopher Dobrian United States	4	162 0.7×	104 0.5×	90 0.6×	16 0.6×	7 0.3×	10	209
Christopher Harte United Kingdom	6	289 1.2×	363 1.6×	119 0.7×	39 1.6×	6 0.3×	15	407
Μάξιμος Καλιακάτσος-Παπακώστας Greece	8	133 0.5×	110 0.5×	117 0.7×	24 1.0×	17 0.8×	40	211

Countries citing papers authored by Esteban Maestre

Since Specialization

Citations

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

Fields of papers citing papers by Esteban Maestre

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Esteban Maestre. 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 Esteban Maestre. The network helps show where Esteban Maestre may publish in the future.

Co-authorship network of co-authors of Esteban Maestre

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Maestre, Esteban, et al.. (2022). Contemporary music genre rhythm generation with machine learning. SHILAP Revista de lepidopterología. 1(1). 1 indexed citations

Maestre, Esteban, Gary Scavone, & Julius O. Smith. (2021). State-space modeling of sound source directivity: An experimental study of the violin and the clarinet. The Journal of the Acoustical Society of America. 149(4). 2768–2781. 3 indexed citations

Maestre, Esteban, et al.. (2015). Playability of a bowed string physical model including finite-width thermal friction and hair dynamics. The Journal of the Acoustical Society of America. 138(3_Supplement). 1887–1887. 1 indexed citations

Maestre, Esteban, Gary Scavone, & Julius O. Smith. (2015). Digital modeling of string instrument bridge reflectance and body radiativity for sound synthesis by digital waveguides. Repositori digital de la UPF (Universitat Pompeu Fabra). 1 2. 1–5. 1 indexed citations

Pérez, Alfonso, et al.. (2011). A Hair Ribbon Deflection Model for Low-intrusiveness Measurement of Bow Force in Violin Performance. New Interfaces for Musical Expression. 481–486. 3 indexed citations

Maestre, Esteban, et al.. (2011). Acquisition and study of blowing pressure profiles in recorder playing. New Interfaces for Musical Expression. 124–127. 2 indexed citations

Villavicencio, Fernando & Esteban Maestre. (2010). GMM-PCA based speaker-timbre conversion on full-quality speech.. SSW. 56–61. 3 indexed citations

Maestre, Esteban, Alfonso Pérez, & Rafael Ramírez. (2010). Gesture Sampling For Instrumental Sound Synthesis: Violin Bowing As A Case Study. The Journal of the Abraham Lincoln Association. 2010. 3 indexed citations

Maestre, Esteban & Rafael Ramírez. (2010). An approach to predicting bowing control parameter contours in violin performance. Intelligent Data Analysis. 14(5). 587–599. 2 indexed citations

10.

Bonada, Jordi, et al.. (2009). Calibration Method to Measure Accurate Bow Force for Real Violin Performances. International Computer Music Conference. 2009(8). e6570–e6570. 6 indexed citations

11.

Maestre, Esteban. (2009). Data-Driven Stastical Modeling of Violin Bowing Gesture Parameter Contours. The Journal of the Abraham Lincoln Association. 2009. 2 indexed citations

12.

Pérez, Alfonso, et al.. (2008). EXPRESSIVE IRISH FIDDLE PERFORMANCE MODEL INFORMED WITH BOWING. The Journal of the Abraham Lincoln Association. 2008. 2 indexed citations

13.

Ramírez, Rafael, Alfonso Pérez, Esteban Maestre, et al.. (2008). Modeling Celtic Violin Expressive Performance. International Conference on Machine Learning. 1 indexed citations

14.

Maestre, Esteban, et al.. (2007). Acquisition of violin instrumental gestures using a commercial EMF device. International Computer Music Conference. 14 indexed citations

15.

Maestre, Esteban, et al.. (2007). ACQUISITION OF VIOLIN INSTRUMENTAL GESTURES USING A COMMERCIAL EMF TRACKING DEVICE. The Journal of the Abraham Lincoln Association. 2007. 14 indexed citations

16.

Bonada, Jordi, Esteban Maestre, & Óscar Mayor. (2006). Modeling Musical Artculation Gestures in Singing Voice Performances. Journal of the Audio Engineering Society. 1 indexed citations

17.

Maestre, Esteban, et al.. (2006). Using Concatenative Synthesis for Expressive Performance in Jazz Saxophone. International Computer Music Conference. 2006(5). 551–62. 5 indexed citations

18.

Ramírez, Rafael, et al.. (2006). A sequential covering evolutionary algorithm for expressive music performance. Innovative Applications of Artificial Intelligence. 1830–1835. 1 indexed citations

19.

Ramírez, Rafael, et al.. (2005). INTRA-NOTE FEATURES PREDICTION MODEL FOR JAZZ SAXOPHONE PERFORMANCE. The Journal of the Abraham Lincoln Association. 2005. 5 indexed citations

20.

Gómez, Emília & Esteban Maestre. (2005). Automatic Characterization of Dynamics and Articulation of Expressive Monophone Recordings. Journal of the Audio Engineering Society. 7 indexed citations

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.

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