Multi Source Collection Method of Service QoS Data for Intelligent Business English Teaching System

The on-demand recognition capability of business English teaching services is crucial for providing an efficient learning experience. However, the existing problem is that network hosts are unable to accurately identify business English teaching data samples, leading to the occurrence of mixed data samples. To address this issue, we have designed a Quality of Service (QoS) data multi-source collection method for intelligent business English teaching system services. By improving the development functionality of Windows Embedded Compact (CE) and defining Analog-to-Digital Converter (ADC) driven service behavior, we have achieved research on the service mode of the intelligent business English teaching system. Based on this, we have set up a teaching data reception module and combined it with a chain processing mechanism for QoS data to determine the actual value range of multi-source parsing parameters, completing the design of the multi-source data collection method for QoS data in the intelligent business English teaching system. The experimental results show that under the effect of the above methods, the recognition result of the network host for the length of teaching data samples is exactly the same as its standard length, which can better solve the problem of mixing teaching data samples and ensure the on-demand recognition ability of the network host for business English teaching services.