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An experiment on an automated literature survey of data-driven speech enhancement methods
Communication Acoustics Lab, School of Electrical and Computer Engineering, Universidade Estadual de Campinas.ORCID iD: 0000-0002-3989-7105
NeuralMind.ORCID iD: 0000-0001-5478-438X
NeuralMind.ORCID iD: 0000-0002-2600-6035
Communication Acoustics Lab, School of Electrical and Computer Engineering, Universidade Estadual de Campinas.ORCID iD: 0000-0002-2246-4450
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2024 (English)In: Acta Acustica, E-ISSN 2681-4617, Vol. 8, no 2, p. 1-8Article in journal (Refereed) Published
Abstract [en]

The increasing number of scientific publications in acoustics, in general, presents difficulties in conducting traditional literature surveys. This work explores the use of a generative pre-trained transformer (GPT) model to automate a literature survey of 117 articles on data-driven speech enhancement methods. The main objective is to evaluate the capabilities and limitations of the model in providing accurate responses to specific queries about the papers selected from a reference human-based survey. While we see great potential to automate literature surveys in acoustics, improvements are needed to address technical questions more clearly and accurately.

Place, publisher, year, edition, pages
EDP Sciences , 2024. Vol. 8, no 2, p. 1-8
Keywords [en]
Speech enhancement methods, Data-driven acoustics, Literature survey, Natural language processing, Large language models
National Category
Language Technology (Computational Linguistics) Fluid Mechanics and Acoustics
Research subject
Speech and Music Communication; Computer Science; Applied and Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-342037DOI: 10.1051/aacus/2023067ISI: 001138798100002Scopus ID: 2-s2.0-85182670204OAI: oai:DiVA.org:kth-342037DiVA, id: diva2:1825843
Note

QC 20240111

Available from: 2024-01-10 Created: 2024-01-10 Last updated: 2024-03-18Bibliographically approved

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fulltext(665 kB)58 downloads
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Sander Tavallaey, ShivaZea, Elias

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dos Santos, ArthurPereira, JayrNogueira, RodrigoMasiero, BrunoSander Tavallaey, ShivaZea, Elias
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Language Technology (Computational Linguistics)Fluid Mechanics and Acoustics

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Citation style
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  • de-DE
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