Martín Hagmüller

46 papers receiving 310 citations

Peers

Martín Hagmüller
Comparison fields: 5 of 45
  • Signal Processing 169
  • Artificial Intelligence 139
  • Physiology 96
  • Computer Vision and Pattern Recognition 83
  • Experimental and Cognitive Psychology 55
Replace Tolga Çiloğlu with:
Tolga Çiloğlu Türkiye
Hoirin Kim South Korea
B.M.G. Cheetham United Kingdom
Krzysztof Marasek Poland
Ańıbal Ferreira Portugal
Biswajit Karan India
D. Govind India
Bartosz Ziółko Poland
S.W. Beet United Kingdom
Akira Sasou Japan
Martín Hagmüller relative to Tolga Çiloğlu Türkiye Tolga Çiloğlu's profile →
Citations per field
00.5×7.5×
Tolga Çiloğlu · 1×
Citations per year

Countries citing papers authored by Martín Hagmüller

Since Specialization
Citations

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

Fields of papers citing papers by Martín Hagmüller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martín Hagmüller

This figure shows the co-authorship network connecting the top 25 collaborators of Martín Hagmüller. A scholar is included among the top collaborators of Martín Hagmüller 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 Martín Hagmüller. Martín Hagmüller 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 0
2 8
3
AMISCO: The Austrian German Multi-Sensor Corpus
1
4 6
5 18
6 3
7 8
8
Differentiating Diplophonia from other Types of Severe Dysphonia by Acoustic Analysis
1
9
Wake-up-word spotting for mobile systems
6
10 7
11 3
12 8
13
The 2nd CHiME Speech Separation and Recognition Challenge: Approaches on Single-Channel Speech Separation and Model-Driven Speech Enhancement
2
14 4
15 2
16 13
17 30
18
Evaluation of the Human Voice for Indications of Workload Induced Stress in the Aviation Environment
15
19 1
20
Poincare Sections for Pitch Mark Determination in Dysphonic Speech
3

About Martín Hagmüller

Martín Hagmüller is a scholar working on Signal Processing, Experimental and Cognitive Psychology and Speech and Hearing, having authored 47 papers that have together received 323 indexed citations. Recurring topics across this work include Speech and Audio Processing (23 papers), Speech Recognition and Synthesis (16 papers) and Voice and Speech Disorders (14 papers). The work is most often cited by research in Signal Processing (169 citations), Artificial Intelligence (139 citations) and Experimental and Cognitive Psychology (55 citations). Martín Hagmüller has collaborated with scholars based in Austria, Germany and United States. Frequent co-authors include Gernot Kubin, Marcos Faúndez-Zanuy, Anna Fuchs, Franz Pernkopf, Berit Schneider‐Stickler, Wolfgang Bigenzahn, Jean Schoentgen, Barbara Schuppler, Matthias Leonhard and Freyja‐Maria Smolle‐Jüttner. Their work appears in journals such as Pattern Recognition, IEEE Journal of Selected Topics in Signal Processing and Journal of Voice.

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