Riccardo Fusaroli


2022

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Identifying stable speech-language markers of autism in children: Preliminary evidence from a longitudinal telephony-based study
Sunghye Cho | Riccardo Fusaroli | Maggie Rose Pelella | Kimberly Tena | Azia Knox | Aili Hauptmann | Maxine Covello | Alison Russell | Judith Miller | Alison Hulink | Jennifer Uzokwe | Kevin Walker | James Fiumara | Juhi Pandey | Christopher Chatham | Christopher Cieri | Robert Schultz | Mark Liberman | Julia Parish-morris
Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology

This study examined differences in linguistic features produced by autistic and neurotypical (NT) children during brief picture descriptions, and assessed feature stability over time. Weekly speech samples from well-characterized participants were collected using a telephony system designed to improve access for geographically isolated and historically marginalized communities. Results showed stable group differences in certain acoustic features, some of which may potentially serve as key outcome measures in future treatment studies. These results highlight the importance of eliciting semi-structured speech samples in a variety of contexts over time, and adds to a growing body of research showing that fine-grained naturalistic communication features hold promise for intervention research.

2021

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The Danish Gigaword Corpus
Leon Strømberg-Derczynski | Manuel Ciosici | Rebekah Baglini | Morten H. Christiansen | Jacob Aarup Dalsgaard | Riccardo Fusaroli | Peter Juel Henrichsen | Rasmus Hvingelby | Andreas Kirkedal | Alex Speed Kjeldsen | Claus Ladefoged | Finn Årup Nielsen | Jens Madsen | Malte Lau Petersen | Jonathan Hvithamar Rystrøm | Daniel Varab
Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)

Danish language technology has been hindered by a lack of broad-coverage corpora at the scale modern NLP prefers. This paper describes the Danish Gigaword Corpus, the result of a focused effort to provide a diverse and freely-available one billion word corpus of Danish text. The Danish Gigaword corpus covers a wide array of time periods, domains, speakers’ socio-economic status, and Danish dialects.