Wuggy: A multilingual pseudoword generator
By Emmanuel Keuleers, Marc Brysbaert. Behavior Research Methods, 2010
657 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Developmental and Educational Psychology
View Paper: https://www.semanticscholar.org/paper/c6e54994c6cf41150ee1eb10a75a1c2cab35f9a4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Emmanuel Dupoux
- Evgeny Kharitonov
- Herman Kamper
- Tu Nguyen
- Wei-Ning Hsu
- Marc Brysbaert
- Morgane Rivière
- Paweł Mandera
In Developmental and Educational Psychology
- Marc Brysbaert
- Emmanuel Keuleers
- Paweł Mandera
- Jonathan Grainger
- Ton Dijkstra
- Boris New
- David Peeters
- Herman Kamper
Citations in the corpus
- Analyzing Speaker Information in Self-Supervised Models to Improve Zero-Resource Speech Processing (2021, methodology): “The set consists of 40k word/non-word pairs, generated using WUGGY [31] and synthesized using Google Cloud Text-to-Speech.”
- The Zero Resource Speech Challenge 2021: Spoken Language Modelling (2021, methodology): “The nonwords are produced with WUGGY [7], which generates, for a given word, a list of candidate nonwords best matched in phonotactics and syllabic structure, which we additionally filtered for pronouncability using G2P, and for having on average the same unigram and bigram phoneme frequencies as wo”
- How Many Words Do We Know? Practical Estimates of Vocabulary Size Dependent on Word Definition, the Degree of Language Input and the Participant’s Age (2016, methodology): “The non-words were generated with the Wuggy algorithm (Keuleers and Brysbaert, 2010).”
- SUBTLEX-NL: A new measure for Dutch word frequency based on film subtitles (2010, methodology): “A few decades later, Kukera and Francis (1967; KF) published a list (also for American English) that would become the frequency measure of choice for language researchers up to the present ( Brysbaert & New, 2009 ).”
- The representation and processing of identical cognates by late bilinguals: RT and ERP effects (2013, methodology): “Nonwords were constructed by Wuggy (Keuleers & Brysbaert, 2010) by changing one to four letters of these existing English nouns, in line with English orthotactics.”
- Revealing the co-existence of written and spoken language coding neural populations in the visual word form area (2025, unknown): “Ninety-six words were selected from the database and 96 pseudowords were generated by Wuggy ( Keuleers & Brysbaert, 2010), using the same phonemes as in the words.”