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Speech Recognition for Inventory Management in Small Businesses

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Authors
Tiglla-Arrascue, Bruno
Huerta-Pahuacho, Junior
Canaval, Luis
Issue Date
2024-01-01
Keywords
Deep Learning
Machine Learning
Speech-to-Text

Metadata
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Publisher
Science and Technology Publications, Lda
Journal
ICSBT International Conference on Smart Business Technologies
URI
http://hdl.handle.net/10757/676030
DOI
https://doi.org/10.5220/0012813600003764
Abstract
In recent years, we have seen an increase in independent businesses working primarily focused on online sales, where they offer products through ads and manage the business with electronic tools. This could leave behind some traditional businesses, especially those that are managed by a single family, where the adaption of new technologies is slower than new business. That's why we want to give them a tool that it's easy to control, a virtual assistant where they can manage the inventory even if they don't know about databases. For this work, we propose to create a speech-to-text platform with machine learning so those users who have difficulties adapting to these new tools can use their voice to command the database and have first contact with these new technologies. Through a fine-tuning process to a pre-trained speech-to-text model in Spanish, we managed to obtain a percentage error result lower than the model used, this being 14.3%, this means that our model has a better accuracy in the context of a Peruvian convenience store. Copyright
Type
info:eu-repo/semantics/article
Rights
info:eu-repo/semantics/embargoedAccess
Language
eng
ISSN
2184772X
ae974a485f413a2113503eed53cd6c53
https://doi.org/10.5220/0012813600003764
Scopus Count
Collections
Seccion en procesamiento

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