首页> 外文会议>Annual Conference of the International Speech Communication Association >Does She Speak RTT? Towards an Earlier Identification of Rett Syndrome Through Intelligent Pre-linguistic Vocalisation Analysis
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Does She Speak RTT? Towards an Earlier Identification of Rett Syndrome Through Intelligent Pre-linguistic Vocalisation Analysis

机译:她说rtt吗?通过智能前语言声学分析,迄今对Rett综合征的早期鉴定

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For many years, an apparently normal early development has been regarded as a main characteristic of Rett syndrome (RTT), a severe progressive neurodevelopmental disorder almost exclusively affecting girls/females. The speech-language domain represents a key domain for the clinical diagnosis of RTT, which usually happens around three years of age. Recent studies have built upon the assumption that this domain is already affected in the prodromal period. Aiming to find RTT-specific speech-language atypicalities on signal level as early acoustic markers, we analysed more than 16 hours of home video recordings of 4 girls later diagnosed with RTT and 4 typically developing girls aged 6 to 12 months. We segmented a total of 4 678 pre-linguistic vocalisations. A comprehensive set of acoustic features was extracted from the vocalisations as basis for the classification paradigm RTT versus typical development. A promising mean unweighted recognition accuracy of 76.5% was achieved using linear kernel support vector machines and 4-fold leave-one-speaker-pair-out cross-validation. To the best of our knowledge, this is the first approach to automatically identify infants later diagnosed with RTT based on acoustic characteristics of pre-linguistic vocalisations. Our findings may build the basis for facilitating earlier identification and thus an avenue for an earlier entry into intervention.
机译:多年来,显然正常的早期发展被视为Rett综合征(RTT)的主要特征,其严重的进行性神经发育障碍几乎完全影响女孩/女性。语音域表示RTT的临床诊断的关键领域,这通常发生在三岁的左右。最近的研究已经建立在假设该领域已经在前期受到影响。旨在在信号级别寻找RTT特定的语言非典型作为早期声学标记,我们分析了超过16小时的家庭视频录制,稍后被诊断出患有RTT和4岁的典型的女孩6至12个月。我们共分割了4 678次语言前声学。从声音中提取了一系列综合声学特征,作为分类范式RTT与典型发展的基础。使用线性内核支持向量机和4倍的休假 - 一对交叉验证,实现了优先的平均未加权识别准确度76.5%的76.5%。据我们所知,这是第一种自动识别患有诊断患有RTT的婴儿的方法,基于前语言的声音的声学特征。我们的调查结果可以为促进早期识别的依据,从而构建促进识别的渠道,以便进入干预措施。

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