汉语儿童言语发育水平自动评估关键技术的研究

Automatic Assessment of Speech Development Level of Chinese Children

随着人们生活水平和大众文化程度的不断提高,许多家庭对早期儿童语言的健康成长越来越关心,迫切需要通过人工智能的方法来自动检测衡量儿童的言语发育水平情况。目前国内儿童语言发育水平的研究尚缺乏统一且有效的检测评估技术手段,在此基础上提出了一种针对自然语言环境下音频分割聚类的改进方法,大大提高了音频分割识别的准确率,这为后续提取表征儿童言语发育水平的特征参数奠定了基础。利用这些特征参数可以对儿童语言的发育情况进行客观、定量的评估,以此促进儿童语言和认知能力的发育。

This paper proposes an improved method of audio segmentation and clustering in natural language environment,which lays a foundation for subsequent extraction of feature parameters representing children's speech development level.These characteristic parameters can be used to evaluate objectively and quantitatively the development quality of children's language,so as to promote the development of children's language and cognitive ability.