If there are more external interference factors in the process of intelligent recognition in English, the recognition accuracy will be greatly reduced. It is of great academic value and application significance to deeply study feature recognition of English part-of-speech and realize automatic image processing of English recognition. Based on unsupervised machine learning and image recognition technology, this study combines the actual factors of English recognition to set the corresponding influencing factors and proposes a reliable method to identify multi-body rotating characters. This method utilizes the principle of the periodic characteristics of the trajectory rotation on the feature space. Moreover, this study conducts a comparative analysis of recognition accuracy by comparative experiments. In addition, this paper analyzes the recognition principles of 4 fonts in detail. The research results show that the proposed method has certain effects and can provide theoretical reference for subsequent related research.

中文翻译：

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基于无监督机器学习和图像识别模型的英语口语特征分析

如果英语智能识别过程中存在更多外部干扰因素，识别精度将大大降低。深入研究英语词性特征识别并实现英语识别的自动图像处理具有重要的学术价值和应用意义。基于无监督机器学习和图像识别技术，结合英语识别的实际因素，设置相应的影响因素，提出了一种可靠的多体旋转字符识别方法。该方法利用了特征空间上轨迹旋转的周期性特征的原理。此外，本研究通过比较实验对识别准确性进行了比较分析。此外，本文详细分析了四种字体的识别原理。研究结果表明，该方法具有一定的效果，可以为后续的相关研究提供理论参考。