Andrew Horner

1.5k total citations
113 papers, 982 citations indexed

About

Andrew Horner is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Andrew Horner has authored 113 papers receiving a total of 982 indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Signal Processing, 67 papers in Computer Vision and Pattern Recognition and 35 papers in Cognitive Neuroscience. Recurrent topics in Andrew Horner's work include Music and Audio Processing (70 papers), Music Technology and Sound Studies (62 papers) and Speech and Audio Processing (39 papers). Andrew Horner is often cited by papers focused on Music and Audio Processing (70 papers), Music Technology and Sound Studies (62 papers) and Speech and Audio Processing (39 papers). Andrew Horner collaborates with scholars based in Hong Kong, United States and Germany. Andrew Horner's co-authors include James W. Beauchamp, Bin Wu, David E. Goldberg, Lippold Haken, Erheng Zhong, Qiang Yang, Chung Lee, Richard H. Y. So, Xiaohan Du and Qingbin Zheng and has published in prestigious journals such as The Journal of the Acoustical Society of America, Human Factors The Journal of the Human Factors and Ergonomics Society and Ergonomics.

In The Last Decade

Andrew Horner

96 papers receiving 884 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew Horner Hong Kong 14 502 420 359 250 173 113 982
Huijuan Yang Singapore 15 164 0.3× 321 0.8× 301 0.8× 86 0.3× 59 0.3× 65 917
Hyunsin Park South Korea 9 128 0.3× 114 0.3× 159 0.4× 377 1.5× 96 0.6× 16 659
Kejun Zhang China 16 195 0.4× 191 0.5× 147 0.4× 130 0.5× 165 1.0× 91 1.5k
Bashir I. Morshed United States 16 234 0.5× 88 0.2× 527 1.5× 512 2.0× 74 0.4× 116 1.4k
Chang Gao China 19 88 0.2× 230 0.5× 94 0.3× 221 0.9× 214 1.2× 70 1.1k
Camille Goudeseune United States 9 166 0.3× 177 0.4× 85 0.2× 86 0.3× 51 0.3× 23 426
Zhigang Yang China 15 54 0.1× 67 0.2× 120 0.3× 172 0.7× 202 1.2× 89 905
Md. Foisal Hossain Bangladesh 14 62 0.1× 179 0.4× 155 0.4× 57 0.2× 66 0.4× 56 587
Sabah M. Ahmed Egypt 17 125 0.2× 86 0.2× 214 0.6× 172 0.7× 23 0.1× 50 933
Adrian Freed United States 14 368 0.7× 543 1.3× 306 0.9× 42 0.2× 20 0.1× 67 688

Countries citing papers authored by Andrew Horner

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Horner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Horner

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Horner. A scholar is included among the top collaborators of Andrew Horner 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 Andrew Horner. Andrew Horner 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
1.
Song, Wenyi, et al.. (2024). A comparative study of the emotional characteristics of violin and erhu musical excerpts: Influence of playing techniques and instrument. The Journal of the Acoustical Society of America. 155(3_Supplement). A61–A61.
2.
Horner, Andrew, et al.. (2023). An automated pop song mashup system using drum swapping. Proceedings of meetings on acoustics. 52. 35009–35009.
3.
Song, Wenyi & Andrew Horner. (2022). Uncovering the differences between the violin and erhu musical instruments by statistical analysis of multiple musical pieces. Proceedings of meetings on acoustics. 50. 50005–50005. 2 indexed citations
4.
Ma, Xiaojuan, et al.. (2019). The Acoustic Features and Their Relationship to the Emotional Characteristics of Rain Sound Effects. Rare & Special e-Zone (The Hong Kong University of Science and Technology).
5.
Horner, Andrew, et al.. (2018). The Effects of Mode, Pitch, and Dynamics on Valence in Piano Scales and Chord Progressions. Sunderland Repository (University of Sunderland).
6.
Horner, Andrew, et al.. (2017). A Study of What Makes Calm and Sad Music So Difficult to Distinguish in Music Emotion Recognition.. The Journal of the Abraham Lincoln Association. 413. 1 indexed citations
7.
Wu, Bin, et al.. (2016). The Effects of Reverberation Time and Amount on the Emotional Characteristics. Sunderland Repository (University of Sunderland). 12. 2 indexed citations
8.
Wu, Bin, et al.. (2014). Beatsens' solution for MediaEval 2014 emotion in music task. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3 indexed citations
9.
Wu, Bin, Andrew Horner, & Chung Lee. (2014). EMOTIONAL PREDISPOSITION OF MUSICAL INSTRUMENT TIMBRES WITH STATIC SPECTRA. International Symposium/Conference on Music Information Retrieval. 253–258. 8 indexed citations
10.
Lee, Chung, Andrew Horner, & Bin Wu. (2013). The Effect of MP3 Compression on the Timbre Space of Sustained Musical Instrument Tones. Journal of the Audio Engineering Society. 61(11). 840–849. 2 indexed citations
11.
Horner, Andrew, James W. Beauchamp, & Richard H. Y. So. (2011). Evaluation of Mel-Band and MFCC-Based Error Metrics for Correspondence to Discrimination of Spectrally Altered Musical Instrument Sounds*. Journal of the Audio Engineering Society. 59(5). 290–303. 8 indexed citations
12.
Horner, Andrew, et al.. (2005). SYNTHESIZING A JAVANESE GONG AGENG. The Journal of the Abraham Lincoln Association. 2005. 1 indexed citations
13.
Horner, Andrew, et al.. (2004). A Comparison between Local Search and Genetic Algorithm Methods forWavetable Matching. The Journal of the Abraham Lincoln Association. 2004. 4 indexed citations
14.
Horner, Andrew, et al.. (2002). Wavetable matching of inharmonic string tones. Journal of the Audio Engineering Society. 50. 46–56. 2 indexed citations
15.
Horner, Andrew, et al.. (2001). Perceptual Wavetable Matching for Synthesis of Musical Instrument Tones. The Journal of the Abraham Lincoln Association. 1 indexed citations
16.
Horner, Andrew, et al.. (1997). Hybrid sampling-wavetable synthesis with genetic algorithms. Journal of the Audio Engineering Society. 45(5). 316–330. 3 indexed citations
17.
Rossiter, David G. & Andrew Horner. (1996). Visualization and manipulation of 3D digital waveguide structures for sound experimentation. The Journal of the Abraham Lincoln Association. 1996. 43–46. 2 indexed citations
18.
Horner, Andrew. (1995). Wavetable Matching Synthesis of Dynamic Instruments with Genetic Algorithms. Journal of the Audio Engineering Society. 43(11). 916–931. 7 indexed citations
19.
Beauchamp, James W. & Andrew Horner. (1992). Extended Nonlinear Waveshaping Analysis/Synthesis Technique. The Journal of the Abraham Lincoln Association. 1992. 4 indexed citations
20.
Horner, Andrew & David E. Goldberg. (1991). Genetic Algorithms and Computer-Assisted Music Composition. The Journal of the Abraham Lincoln Association. 1991. 337. 75 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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