Mark Huckvale

2.0k total citations
97 papers, 1.2k citations indexed

About

Mark Huckvale is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology and Signal Processing. According to data from OpenAlex, Mark Huckvale has authored 97 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Artificial Intelligence, 33 papers in Experimental and Cognitive Psychology and 32 papers in Signal Processing. Recurrent topics in Mark Huckvale's work include Speech Recognition and Synthesis (37 papers), Speech and Audio Processing (30 papers) and Phonetics and Phonology Research (29 papers). Mark Huckvale is often cited by papers focused on Speech Recognition and Synthesis (37 papers), Speech and Audio Processing (30 papers) and Phonetics and Phonology Research (29 papers). Mark Huckvale collaborates with scholars based in United Kingdom, Australia and Germany. Mark Huckvale's co-authors include Julian Leff, Alexander Leff, Geoffrey C. Williams, Philippa Garety, Thomas Ward, Mar Rus‐Calafell, Tom Craig, Richard Emsley, Elizabeth Howarth and Peter Howell and has published in prestigious journals such as Nature Medicine, The British Journal of Psychiatry and The Journal of the Acoustical Society of America.

In The Last Decade

Mark Huckvale

91 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Huckvale United Kingdom 17 440 387 293 289 282 97 1.2k
Heidi Christensen United Kingdom 24 316 0.7× 1.1k 2.9× 690 2.4× 261 0.9× 183 0.6× 122 1.9k
Steven R. Livingstone Canada 19 1.0k 2.3× 342 0.9× 760 2.6× 684 2.4× 58 0.2× 32 1.9k
Sebastian Schnieder Germany 9 851 1.9× 332 0.9× 189 0.6× 242 0.8× 79 0.3× 16 1.3k
Jeffrey M. Girard United States 21 1.3k 3.0× 154 0.4× 177 0.6× 536 1.9× 79 0.3× 56 2.2k
Daniel Bone United States 19 288 0.7× 265 0.7× 164 0.6× 499 1.7× 47 0.2× 38 1.0k
Michael S. Cannizzaro United States 10 385 0.9× 160 0.4× 130 0.4× 238 0.8× 67 0.2× 26 940
Emily Mower Provost United States 22 1.1k 2.5× 775 2.0× 722 2.5× 250 0.9× 130 0.5× 73 1.8k
Giota Stratou United States 17 673 1.5× 336 0.9× 55 0.2× 190 0.7× 46 0.2× 25 1.2k
Kathleen Fraser Canada 15 165 0.4× 523 1.4× 53 0.2× 505 1.7× 394 1.4× 61 1.2k
Hélène Lœvenbruck France 19 630 1.4× 145 0.4× 115 0.4× 609 2.1× 66 0.2× 70 1.2k

Countries citing papers authored by Mark Huckvale

Since Specialization
Citations

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

Fields of papers citing papers by Mark Huckvale

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Huckvale

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Huckvale. A scholar is included among the top collaborators of Mark Huckvale 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 Mark Huckvale. Mark Huckvale 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.
Rus‐Calafell, Mar, Tobias Teismann, Silvia Schneider, et al.. (2025). Using Virtual Reality Social Environments to Promote Outcomes' Generalization of AVATAR Therapy for Distressing Voices: A Case Study. Journal of Clinical Psychology. 81(6). 516–525. 2 indexed citations
2.
Edwards, Clementine, Lucy Miller, Hassan Jafari, et al.. (2023). The voice characterisation checklist: psychometric properties of a brief clinical assessment of voices as social agents. Frontiers in Psychiatry. 14. 1192655–1192655. 2 indexed citations
3.
Huckvale, Mark, et al.. (2021). NUVA: A Naming Utterance Verifier for Aphasia Treatment. Computer Speech & Language. 69. 101221–101221. 16 indexed citations
4.
Garety, Philippa, Clementine Edwards, Thomas Ward, et al.. (2021). Optimising AVATAR therapy for people who hear distressing voices: study protocol for the AVATAR2 multi-centre randomised controlled trial. Trials. 22(1). 366–366. 32 indexed citations
5.
6.
Huckvale, Mark, et al.. (2017). On the Predictability of the Intelligibility of Speech to Hearing Impaired Listeners. UCL Discovery (University College London). 1 indexed citations
7.
Craig, Tom, Mar Rus‐Calafell, Thomas Ward, et al.. (2017). AVATAR therapy for auditory verbal hallucinations in people with psychosis: a single-blind, randomised controlled trial. The Lancet Psychiatry. 5(1). 31–40. 248 indexed citations
8.
Huckvale, Mark, et al.. (2015). Predicting Fatigue and Psychophysiological Test Performance from Speech for Safety-Critical Environments. Frontiers in Bioengineering and Biotechnology. 3. 124–124. 7 indexed citations
9.
Leff, Julian, et al.. (2013). Computer-assisted therapy for medication-resistant auditory hallucinations: proof-of-concept study. The British Journal of Psychiatry. 202(6). 428–433. 128 indexed citations
10.
Huckvale, Mark. (2011). The KLAIR Toolkit for Recording Interactive Dialogues with a Virtual Infant.. UCL Discovery (University College London). 3341–3342. 1 indexed citations
11.
Huckvale, Mark, et al.. (2010). Signal properties reducing intelligibility of speech after noise reduction. UCL Discovery (University College London). 1914–1918. 2 indexed citations
12.
Huckvale, Mark. (2006). The new accent technologies:recognition, measurement and manipulation of accented speech. UCL Discovery (University College London). 2 indexed citations
13.
Howard, Ian S. & Mark Huckvale. (2005). Training a Vocal Tract Synthesiser to imitate speech using Distal Supervised Learning. UCL Discovery (University College London). 13 indexed citations
14.
Vazquez-Alvarez, Yolanda & Mark Huckvale. (2002). The Reliability of the ITU-P.85 Standard for the Evaluation of Text-to-Speech Systems. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 21 indexed citations
15.
Ortega-Llebaría, Marta, et al.. (2000). Automatic cue-enhancement of natural speech for improved intelligibility.. UCL Discovery (University College London). 4 indexed citations
16.
Eriksson, Anders, et al.. (1999). Tutorial Design for Web-based Teaching and Learning. Scandinavian Journal of Immunology. 52(5). 145–148. 2 indexed citations
17.
Fourcin, Adrian, Björn Granström, Mark Huckvale, et al.. (1995). EUROM-A Spoken Language Resource for the EU. Conference of the International Speech Communication Association. 1. 867–870. 72 indexed citations
18.
Holmes, Wendy & Mark Huckvale. (1994). WHY HAVE HMMS BEEN SO SUCCESSFUL FOR AUTOMATIC SPEECH RECOGNITION AND HOW MIGHT THEY BE IMPROVED. UCL Discovery (University College London). 184(1). 1–14. 5 indexed citations
19.
Howard, Ian S. & Mark Huckvale. (1989). Two-level recognition of isolated word using neural nets. PEARL (University of Plymouth). 90–94. 1 indexed citations
20.
Huckvale, Mark, et al.. (1987). The SPAR speech filing system. 1305–1308. 14 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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