The difficulty of sports video detection technology lies in how to detect the end point segment from the complex video speech environment, and the artificial intelligence technology is still in the research stage. Based on this, this study builds a model based on the hidden Markov model. At the same time, the video file noise reduction processing is performed by the spectral subtraction noise reduction algorithm of the complex domain extension. Moreover, combined with the actual situation of sports competitions, this paper proposes an endpoint detection algorithm based on variance characteristics, and comprehensively designs a speech recognition model based on Markov model. In order to verify the validity of the model, the performance of the model is verified by an example, and the real sports competition is taken as the research object, and the accuracy rate and the recall rate are set as performance indicators. The research shows that the model proposed in this study performs well in both accuracy and performance rate and can be used as a reference for artificial intelligence application to sports video detection technology.

运动视频检测技术的难点在于如何从复杂的视频语音环境中检测出端点片段，而人工智能技术仍处于研究阶段。在此基础上，本研究建立了基于隐马尔可夫模型的模型。同时，视频文件的降噪处理是通过复数域扩展的频谱减法降噪算法执行的。此外，结合体育比赛的实际情况，提出了一种基于方差特征的终点检测算法，并综合设计了基于马尔可夫模型的语音识别模型。为了验证模型的有效性，通过实例验证了模型的性能，并以真实的体育比赛为研究对象，将准确率和召回率设置为性能指标。研究表明，该模型提出的模型在准确性和性能上均具有良好的性能，可作为人工智能在体育视频检测技术中的参考。