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An investigation of linguistic stress and articulatory vowel characteristics for automatic depression classification

机译:自动抑郁分类的语言应力和发音元音特征研究

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The effects of psychomotor retardation associated with clinical depression are linked to a reduction in variability in acoustic parameters. However, linguistic stress differences between non-depressed and clinically depressed individuals have yet to be investigated. In this paper, by examining vowel articulatory parameters, statistically significant differences in articulatory characteristics are found at a paraphonetic level. For articulatory characteristic features, tongue height and advancement in terms of 'mid' and 'front' vowel sets show similar depression classification performance trends for both the DAIC-WOZ (English) and AViD (German) databases. Considering linguistic stress feature components, for both databases, depressed speakers exhibit shorter vowel durations and less variance for 'low', 'back', and 'rounded' vowel positions. Results for the DAIC-WOZ and AViD datasets using a small set of linguistic stress based features derived from multiple vowel articulatory parameter sets show absolute, statistically significant, gains of 7% and 20% in two-class depression classification performance over baseline approaches. Linguistic stress feature results indicate that specific vowel set analysis provides better discrimination of clinically depressed and non-depressed speakers. Knowledge gleaned from this research allows the design of more effective automatic depression disorder classification systems. (C) 2018 Elsevier Ltd. All rights reserved.
机译:与临床抑郁症相关的精神运动迟缓的影响与声学参数变异性的降低有关。然而,尚未研究非抑郁者和临床抑郁者之间的语言压力差异。在本文中,通过检查元音发音参数,可以发现在副音水平上发音特征在统计学上有显着差异。对于发音特征,在DAIC-WOZ(英语)和AViD(德语)数据库中,舌头高度和“中”和“前”元音集的进步都表现出相似的抑郁分类表现趋势。考虑到语言压力特征成分,对于这两个数据库,沮丧的讲话者表现出较短的元音持续时间,并且对于“低”,“后”和“圆”元音位置的变化较小。 DAIC-WOZ和AViD数据集的结果使用了一小组基于语言应力的特征,这些特征是基于多个元音发音参数集而得出的,与基线方法相比,两类抑郁症分类的绝对值(统计上显着)提高了7%和20%。语言压力特征结果表明,特定的元音集分析可以更好地区分临床上抑郁的和非抑郁的说话者。从这项研究中获得的知识可以设计出更有效的抑郁症自动分类系统。 (C)2018 Elsevier Ltd.保留所有权利。

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