Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati, Assam 781039, India.
Department of Electronics, All India Institute of Speech and Hearing, Mysuru 570006, India.
J Acoust Soc Am. 2019 Aug;146(2):1164. doi: 10.1121/1.5121310.
Assessment of intelligibility is required to characterize the overall speech production capability and to measure the speech outcome of different interventions for individuals with cleft lip and palate (CLP). Researchers have found that articulation error and hypernasality have a significant effect on the degradation of CLP speech intelligibility. Motivated by this finding, the present work proposes an objective measure of sentence-level intelligibility by combining the information of articulation deficits and hypernasality. These two speech disorders represent different aspects of CLP speech. Hence, it is expected that the composite measure based on them may utilize complementary clinical information. The objective scores of articulation and hypernasality are used as features to train a regression model, and the output of the model is considered as the predicted intelligibility score. The Spearman's correlation coefficient based analysis shows a significant correlation between the predicted and perceptual intelligibility scores (ρ = 0.77, p < 0.001).
评估清晰度是为了描述整体言语产生能力,并衡量不同腭裂(CLP)干预措施的言语结果。研究人员发现,发音错误和超鼻音对 CLP 语音清晰度的降低有显著影响。受此发现的启发,本工作提出了一种基于结合发音缺陷和超鼻音信息的句子级可理解性的客观度量。这两种言语障碍代表了 CLP 言语的不同方面。因此,预计基于它们的组合度量可能会利用互补的临床信息。发音和超鼻音的客观分数用作特征来训练回归模型,模型的输出被认为是预测的可理解性分数。基于 Spearman 相关系数的分析显示,预测和感知可理解性得分之间存在显著相关性(ρ=0.77,p<0.001)。