自动语音处理软件——评估鼻音的新敏感工具:初步研究

K. Girish, M. Pushpavathi, Ajish K. Abraham, C. Vikram
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摘要

简介:自动语音处理(ASP)软件是一种鼻音评估工具。ASP研究集中于调查句子以发现鼻音,并将ASP分数与其他测量鼻音的客观评估分数相关联,这一研究很少。因此,本研究旨在比较ASP软件和鼻测量仪在不同刺激下对典型发育中儿童(TDC)和腭裂修复儿童(RCP)的鼻测量值。方法:参与者包括30名讲卡纳达语的TDC和10名患有RCP的儿童(9-12岁)。记录言语刺激(口腔、鼻腔和口鼻句子),并从ASP软件和鼻测量仪中获得值。采用以下统计检验:混合方差分析、重复测量方差分析、配对样本t检验、独立样本t检验和皮尔逊相关性。结果:与鼻测量仪一样,ASP软件的鼻腔数值在两种人群中都较高,其次是口鼻句和口语句。在所有刺激中,患有RCP的儿童的鼻塞值都高于TDC。TDC中的口鼻句子和RCP中的鼻句子和口鼻句子中的仪器之间的鼻音值存在显著差异。在两组中,鼻测量仪和ASP软件之间的刺激值没有显示出显著的相关性。结论:ASP软件能够成功地识别TDC和RCP患儿的鼻腔。然而,需要解决的一个主要问题是软件的动态范围,它必须在大量人群中进行验证。
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Automatic speech processing software – New sensitive tool for the assessment of nasality: A preliminary study
Introduction: Automatic speech processing (ASP) software is a nasality assessment tool. ASP studies focusing on investigating sentences to find nasality and correlating ASP scores with other objective assessment scores measuring nasality are scarce. Hence, the present study aimed at comparing the nasalance values of the ASP software with the nasometer in typically developing children (TDC) and children with repaired cleft palate (RCP) across different stimuli. Methods: Participants included 30 Kannada speaking TDC and 10 children with RCP (9–12 years). Speech stimuli (oral, nasal, and oronasal sentences) were recorded and the values were obtained from the ASP software as well as the nasometer. The following statistical tests were applied: mixed ANOVA, repeated measures ANOVA, paired samples t-test, independent samples t-test and Pearson's correlation. Results: Like nasometer, the nasalance values of ASP software were high for the nasal sentences followed by the oronasal sentences and the oral sentences, for both the populations. Higher nasalance values were found for children with RCP than for TDC across all the stimuli. Significant differences were found in nasalance values between the instruments in oral and oronasal sentences in TDC and nasal sentences and oronasal sentences in RCP. The nasalance values across the stimuli between nasometer and ASP software in both the groups showed no significant correlations. Conclusions: ASP software was successful in identifying nasalance in TDC and children with RCP. However, a major issue needs to be addressed concerning the dynamic range of the software and it has to be validated on a large number of populations.
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