Full description of an automated pipeline for providing personalized feedback based on audio samples

Peurey, Loann; Havard, William; Virlet, Gwendal; Cao, Xuan-Nga; Bloomfield, Juanita; Balsa, Ana; Cid, Alejandro; Ottavianelli, Martín; Horta Brasil, José Luis; Cristia, Alejandrina

dc.rights.license	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.contributor.author	Peurey, Loann
dc.contributor.author	Havard, William
dc.contributor.author	Virlet, Gwendal
dc.contributor.author	Cao, Xuan-Nga
dc.contributor.author	Bloomfield, Juanita
dc.contributor.author	Balsa, Ana
dc.contributor.author	Cid, Alejandro
dc.contributor.author	Ottavianelli, Martín
dc.contributor.author	Horta Brasil, José Luis
dc.contributor.author	Cristia, Alejandrina
dc.date.accessioned	2026-05-15T14:17:30Z
dc.date.available	2026-05-15T14:17:30Z
dc.date.issued	2024	es
dc.identifier.uri	https://hdl.handle.net/20.500.12806/2832
dc.format.extent	7 p	es
dc.format.mimetype	text/plain	es
dc.language	eng	es
dc.publisher	Universidad de Montevideo, Facultad de Ciencias Empresariales y Economía	es
dc.rights	Abierto	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.title	Full description of an automated pipeline for providing personalized feedback based on audio samples	es
dc.type	Artículo	es
dc.type.version	Aceptada	es
dc.description.abstractenglish	Personalized feedback based on the automated analysis of au- dio samples could be useful in a wide range of intervention contexts, from early childhood to neurodegenerative programs, which target behaviors having vocal correlates. In this paper, we describe an automated pipeline that allows one to provide personalized feedback based on the automated analysis of au- dio samples of caregiver-child conversations captured using a smartphone. The pipeline relies on open-source packages and AWS in order to provide a cheap, reproducible, and consider- ably scalable solution for researchers and practitioners inter- ested in early childhood development and caregiver-child in- teraction, and which could be adapted for other use cases. It processes conversation files that are 1-10 minutes long, with a cost of 0.20 US$ per hour of audio analyzed. It is currently op- erational in one large-scale experiment in Uruguay, where audio files are collected through a chatbot, whose implementation is not covered in this paper. Finally, we lay out limitations of our approach and potential improvements.	es
dc.subject.keyword	Automated analyses	es
dc.subject.keyword	Acoustic analyses	es
dc.subject.keyword	Infantparent interaction	es