Matthew P. Aylett

86 papers receiving 1.8k citations

Peers

Matthew P. Aylett
Comparison fields: 5 of 103
  • Artificial Intelligence 1.1k
  • Experimental and Cognitive Psychology 986
  • Language and Linguistics 454
  • Cognitive Neuroscience 411
  • Linguistics and Language 401
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Citations per field
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Citations per year

Countries citing papers authored by Matthew P. Aylett

Since Specialization
Citations

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

Fields of papers citing papers by Matthew P. Aylett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew P. Aylett. 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 Matthew P. Aylett. The network helps show where Matthew P. Aylett may publish in the future.

Co-authorship network of co-authors of Matthew P. Aylett

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew P. Aylett. A scholar is included among the top collaborators of Matthew P. Aylett 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 Matthew P. Aylett. Matthew P. Aylett 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
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Expressive speech synthesis: synthesising ambiguity.
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10 17
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Single Speaker Segmentation and Inventory Selection Using Dynamic Time Warping Self Organization and Joint Multigram Mapping
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14 4
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Merging data driven and rule based prosodic models for unit selection TTS.
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Referential form, word duration, and modelling the listener in spoken dialogue
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8th European Conference on Speech Communication and Technology, EUROSPEECH 2003 - INTERSPEECH 2003, Geneva, Switzerland, September 1-4, 2003
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Proceedings of the Sixth International Conference on Spoken Language Processing
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About Matthew P. Aylett

Matthew P. Aylett is a scholar working on Human-Computer Interaction, Experimental and Cognitive Psychology and Artificial Intelligence, having authored 93 papers that have together received 2.0k indexed citations. Recurring topics across this work include Speech and dialogue systems (39 papers), Speech Recognition and Synthesis (29 papers) and Phonetics and Phonology Research (19 papers). The work is most often cited by research in Linguistics and Language (401 citations), Experimental and Cognitive Psychology (986 citations) and Language and Linguistics (454 citations). Matthew P. Aylett has collaborated with scholars based in United Kingdom, Ireland and United States. Frequent co-authors include Alice Turk, Ellen Gurman Bard, Catherine Sotillo, Alison Newlands, Anne H. Anderson, Gwyneth Doherty‐Sneddon, Yolanda Vazquez-Alvarez, Benjamin R. Cowan, Leigh Clark and Cosmin Munteanu. Their work appears in journals such as PLoS ONE, The Journal of the Acoustical Society of America and Journal of Memory and Language.

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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