Design And Implementation Of Digital Recognition System Of Inventory Machine Based On Deep Learning

Under the influence of the increasing availability of computer computing power and the explosion of data volume brought about by the Internet,the upsurge of artificial intelligence led by deep learning has become more and more intense.Researchers and capital continue to pour into the field of artificial intelligence,solving problems one by one,and continue to promote artificial intelligence products.The traditional inventory system requires manual entry of commodity inventory,which is inefficient and error-prone.This paper studies and designs the digital recognition system of the inventory machine with digital voice recognition as the main body(hereinafter referred to as the voice inventory system).The original intention of the system is Allows inventory staff to directly enter inventory through voice to improve inventory efficiency.This article conducts an in-depth analysis of the requirements of the voice inventory system,determines the design of the system,divides the system into five major functional modules,and designs the functions of each module in detail.In the structural design of the speech recognition model,the generalization ability of the model in actual application scenarios is considered,and the over-fitting problem caused by insufficient training corpus is also considered.At the same time,in order to ensure that the model can continuously improve its recognition accuracy through incremental learning,the system is also designed to collect audio during user use to enrich the corpus.After that,this article conducted a series of training experiments on the digital speech recognition model,and continuously optimized the model based on the analysis of the experimental results.Finally,this article combines the demand analysis and system design of the system,using Flask framework,SQLite database and React technology to develop the voice inventory system,conducts a complete functional test of the system,and examines the digital voice recognition model in actual scenarios.The performance was evaluated,and the paper summarized and forecasted based on the test and evaluation results.The voice inventory system in this paper takes digital voice recognition as the core,designs a simple inventory process to improve inventory efficiency,uses end-to-end speech recognition model structure design to improve recognition efficiency,and implements a series of functions that support models for incremental learning to continue Improve the recognition accuracy of the model.