Abstract
There is often noise in spoken machine English, which affects the accuracy of pronunciation. Therefore, how to accurately detect the noise in machine English spoken language and give standard spoken pronunciation is very important and meaningful. The traditional machine-oriented spoken English speech noise detection technology is limited to the improvement of software algorithm, mainly including speech enhancement technology and speech endpoint detection technology. Based on this, this paper will develop a wireless sensor network based on machine English oral pronunciation noise based on air and nonair conduction, reasonably design and configure air sensors, and nonair conduction sensors to deal with machine English oral pronunciation noise, so as to improve the naturalness and intelligibility of machine English speech. At the hardware level, this paper mainly optimizes the AD sampling, sensor matching layout, and internal hardware circuit board layout of the two types of sensors, so as to solve the compatibility problem between them and further reduce the hardware power consumption. In order to further verify or evaluate the performance of the machine spoken English speech noise detection sensor designed in this paper, a machine spoken English training system based on Android platform is designed. Compared with the traditional system, the training system can improve the intelligence of machine oriented oral English noise detection algorithm, so as to continuously improve the accuracy of system detection. The machine English pronunciation is adjusted and corrected by combining the data sensed by the sensor, so as to form a closed-loop design. The experimental results show that the wireless sensor sample proposed in this paper has obvious advantages in detecting the accuracy of machine English oral pronunciation, and its good closed-loop system is helpful to further improve the accuracy of machine English oral pronunciation.
Highlights
With the continuous development of economic globalization, English, as an important language, plays an important role in the process of globalization
In order to further verify or evaluate the performance of the machine English oral pronunciation noise detection sensor designed in this paper, a machine English oral training system is designed based on Android platform
The machine English pronunciation is adjusted and corrected by combining the data sensed by the sensor, so as to form a closed-loop design
Summary
With the continuous development of economic globalization, English, as an important language, plays an important role in the process of globalization. In order to further improve the accuracy of machine-oriented spoken English pronunciation, there are various traditional noise suppression technologies. The traditional recognition of machine English oral pronunciation noise is too limited to the research and analysis of software algorithm, so it ignores the analysis and development of hardware level of noise detection and training system. The structure of this paper is as follows: in the second section of this paper, the current machine-oriented spoken English pronunciation noise detection technology will be analyzed and studied; in the third section, based on wireless sensor hardware technology, air conduction sensor, and nonair conduction sensor, the noise detection technology of machine-oriented oral English pronunciation is developed, and the corresponding oral English pronunciation training system is given; the fourth section of this paper is mainly validation experiment and analysis; this paper will be summarized
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