Speech Recognition for Inventory Management in Small Businesses
Descripción del Articulo
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 famil...
Autores: | , , |
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Formato: | artículo |
Fecha de Publicación: | 2024 |
Institución: | Universidad Peruana de Ciencias Aplicadas |
Repositorio: | UPC-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorioacademico.upc.edu.pe:10757/676030 |
Enlace del recurso: | http://hdl.handle.net/10757/676030 |
Nivel de acceso: | acceso embargado |
Materia: | Deep Learning Machine Learning Speech-to-Text |
Sumario: | 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 |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).