JOURNAL ARTICLE

Training room management based on speech recognition and artificial intelligence.

  • Published In: International Journal of Modeling, Simulation & Scientific Computing, 2023, v. 14, n. 3. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Xiao, Honglan 3 of 3

Abstract

This paper starts from the basic principles of speech recognition, starting from acoustic models and features, and applies deep convolutional neural networks to speech recognition processing. It also introduces the overall process of speech recognition and mainstream algorithms to classify and summarize the speech recognition system. Due to the technological innovation of speech recognition and offline speech recognition systems, we found that traditional systems have low interactivity, poor flexibility, poor recognition command library, and other problems. We provide solutions for this paper according to the specific application environment. This paper introduces the design and implementation of an artificial intelligence teaching management system based on the Internet of Things (IoT) technology. Based on the design of the entire system, the system databases such as the video surveillance module, artificial intelligence security module, and remote control module are designed and realized the functions of these modules. Finally, RFID technology and database technology will be used to realize the informatization of training room personnel and equipment management, and the positioning and storage inspection of training room equipment. Secondly, from the perspective of environmental monitoring of the training room, temperature/ humidity sensors and optical sensors are used to complete the collection of real-time environmental data in the training room, thereby transmitting the data to the host system. It realizes the pairing through the Zigbee wireless communication module. Real-time monitoring of training room and management system. This paper introduces speech recognition and artificial intelligence into the management system of the training room so that the training can be better recorded and managed. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Modeling, Simulation & Scientific Computing. 2023/06, Vol. 14, Issue 3, p1
  • Document Type:Article
  • Subject Area:Computer Science
  • Publication Date:2023
  • ISSN:17939623
  • DOI:10.1142/S1793962323500046
  • Accession Number:169782892
  • Copyright Statement:Copyright of International Journal of Modeling, Simulation & Scientific Computing is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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