Thomas Drugman

3.5k total citations · 1 hit paper
86 papers, 2.3k citations indexed

About

Thomas Drugman is a scholar working on Artificial Intelligence, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, Thomas Drugman has authored 86 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Artificial Intelligence, 57 papers in Signal Processing and 18 papers in Experimental and Cognitive Psychology. Recurrent topics in Thomas Drugman's work include Speech Recognition and Synthesis (73 papers), Speech and Audio Processing (55 papers) and Music and Audio Processing (30 papers). Thomas Drugman is often cited by papers focused on Speech Recognition and Synthesis (73 papers), Speech and Audio Processing (55 papers) and Music and Audio Processing (30 papers). Thomas Drugman collaborates with scholars based in Belgium, United States and United Kingdom. Thomas Drugman's co-authors include Thierry Dutoit, John Kane, Abeer Alwan, Tuomo Raitio, Stefan Scherer, Gilles Degottex, Barış Bozkurt, Christer Gobl, Yannis Stylianou and Jón Guðnason and has published in prestigious journals such as Neurocomputing, IEEE Signal Processing Letters and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Thomas Drugman

80 papers receiving 2.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

COVAREP — A collaborative voice analysis repository for speech technologies

2014 429 citations Gilles Degottex, John Kane et al. profile →

Peers

Thomas Drugman

AI

SP

ECP

PHYSI

CVPR

Carol Espy-Wilson United States

Heidi Christensen United Kingdom

Tobias Bocklet Germany

K. Sreenivasa Rao India

Tuomo Raitio Finland

John Kane Ireland

Stuart Cunningham United Kingdom

Corinne Fredouille France

Jean‐Pierre Martens Belgium

Shahin Amiriparian Germany

Carol Espy-Wilson United States

Thomas Drugman

2.0k ×1.2

AI

1.9k ×1.4

SP

1.2k ×1.7

ECP

242 ×0.5

PHYSI

233 ×0.9

CVPR

Citations per year, relative to Thomas Drugman Thomas Drugman (= 1×) peers Carol Espy-Wilson

Countries citing papers authored by Thomas Drugman

Since Specialization

Citations

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

Fields of papers citing papers by Thomas Drugman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Drugman

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Drugman. A scholar is included among the top collaborators of Thomas Drugman 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 Thomas Drugman. Thomas Drugman 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

1.

Moinet, Alexis, et al.. (2023). eCat: An End-to-End Model for Multi-Speaker TTS & Many-to-Many Fine-Grained Prosody Transfer. 3387–3391. 1 indexed citations

2.

Moinet, Alexis, et al.. (2023). A Comparative Analysis of Pretrained Language Models for Text-to-Speech. 14–20. 2 indexed citations

3.

Moinet, Alexis, et al.. (2020). CopyCat: Many-to-Many Fine-Grained Prosody Transfer for Neural Text-to-Speech. arXiv (Cornell University). 4387–4391. 43 indexed citations

4.

Moinet, Alexis, et al.. (2017). Phrase Break Prediction for Long-Form Reading TTS: Exploiting Text Structure Information. 1064–1068. 10 indexed citations

5.

Drugman, Thomas, et al.. (2015). Occurrence Frequencies of Acoustic Patterns of Vocal Fry in American English Speakers. Journal of Voice. 30(6). 759.e11–759.e20. 14 indexed citations

6.

Drugman, Thomas, et al.. (2015). Voice Activity Detection: Merging Source and Filter-based Information. IEEE Signal Processing Letters. 23(2). 252–256. 59 indexed citations

7.

Drugman, Thomas, et al.. (2015). HMM-Based Speech Segmentation: Improvements of Fully Automatic Approaches. IEEE/ACM Transactions on Audio Speech and Language Processing. 24(1). 5–15. 26 indexed citations

8.

Drugman, Thomas. (2014). Maximum Phase Modeling for Sparse Linear Prediction of Speech. IEEE Signal Processing Letters. 21(2). 185–189. 13 indexed citations

9.

Degottex, Gilles, John Kane, Thomas Drugman, Tuomo Raitio, & Stefan Scherer. (2014). COVAREP — A collaborative voice analysis repository for speech technologies. 960–964. 429 indexed citations breakdown →

10.

Drugman, Thomas, et al.. (2013). A comparative study of pitch extraction algorithms on a large variety of singing sounds. 7815–7819. 53 indexed citations

11.

Drugman, Thomas, et al.. (2013). A quantitative comparison of glottal closure instant estimation algorithms on a large variety of singing sounds. 1702–1706. 14 indexed citations

12.

Drugman, Thomas, John Kane, Tuomo Raitio, & Christer Gobl. (2013). Prediction of creaky voice from contextual factors. 7967–7971. 4 indexed citations

13.

Kane, John, Thomas Drugman, & Christer Gobl. (2012). Improved automatic detection of creak. Computer Speech & Language. 27(4). 1028–1047. 41 indexed citations

14.

Drugman, Thomas, et al.. (2012). Statistical methods for varying the degree of articulation in new HMM-based voices. 3. 291–296. 1 indexed citations

15.

Drugman, Thomas & Abeer Alwan. (2011). Joint robust voicing detection and pitch estimation based on residual harmonics. 1973–1976. 163 indexed citations

16.

Drugman, Thomas, et al.. (2009). On the mutual information of glottal source estimation techniques for the automatic detection of speech pathologies.. ORBi UMONS. 53–56. 1 indexed citations

17.

Drugman, Thomas, Barış Bozkurt, & Thierry Dutoit. (2009). Complex cepstrum-based decomposition of speech for glottal source estimation. 116–119. 44 indexed citations

18.

Drugman, Thomas, et al.. (2008). Voice source parameters estimation by fitting the glottal formant and the inverse filtering open phase. ORBi UMONS. 1–5. 6 indexed citations

19.

Drugman, Thomas, et al.. (2008). GLOTTAL SOURCE ESTIMATION ROBUSTNESS - A Comparison of Sensitivity of Voice Source Estimation Techniques. 202–207. 6 indexed citations

20.

Drugman, Thomas, et al.. (2007). Relevant Feature Selection for Audio-Visual Speech Recognition. 5. 179–182. 18 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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