Bibliographic citations
Puelles, G., Quezada, J. (2016). Automatización del proceso de la toma de pedidos en el restaurante Don Rulo SAC utilizando una aplicación móvil con reconocimiento de voz soportada por las API´s de Google [Tesis, Universidad Privada Antenor Orrego - UPAO]. https://hdl.handle.net/20.500.12759/3615
Puelles, G., Quezada, J. Automatización del proceso de la toma de pedidos en el restaurante Don Rulo SAC utilizando una aplicación móvil con reconocimiento de voz soportada por las API´s de Google [Tesis]. : Universidad Privada Antenor Orrego - UPAO; 2016. https://hdl.handle.net/20.500.12759/3615
@misc{renati/377181,
title = "Automatización del proceso de la toma de pedidos en el restaurante Don Rulo SAC utilizando una aplicación móvil con reconocimiento de voz soportada por las API´s de Google",
author = "Quezada Espinoza, José Otoniel",
publisher = "Universidad Privada Antenor Orrego - UPAO",
year = "2016"
}
The constant improvement of the customer service process with the current demand for Peruvian food leads to the restaurants in a cycle of continuous improvement in all the processes they carry out to provide a quality product and customer loyalty. This is the case of the restaurant Don Rulo, located in calle las gemas 181, Urb. Santa Ines, Trujillo, Peru; Which already having an information system to automate the order-taking process, still wants to improve the times lost when registering them at the workstation, as well as the queues that are formed at peak hours. In the present investigation the automation of the process of order taking was developed in the restaurant Don Rulo SAC, using a mobile application with voice recognition supported by the APIs of Google. For the development of this automation the ICONIX methodology was used as reference and its adaptation in a functional prototype using the APIs of Google, as well as the block programming project of AppInventor. The prototype for the automation of order taking has been successfully tested, the results of the test carried out, allowed to conclude that with the prototype of order taking using a mobile application with speech recognition supported by the APIs of Google, it makes possible that The ordering process is in average value a difference of 24 seconds, but in a controlled environment. There are several limitations according to the environment, connection, interface or user, but as for example when there is a lot of background noise it is difficult to finish dictating the order, or when there is no internet signal can not connect to Google service. To conclude, we have used statistical tests such as averages, mean and Wilcoxon, which prove our results in the present investigation.
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