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首页> 外文会议>IEEE International Conference on Acoustics, Speech and Signal Processing >Acoustic and Linguistic Analyses to Assess Early-Onset and Genetic Alzheimer’s Disease
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Acoustic and Linguistic Analyses to Assess Early-Onset and Genetic Alzheimer’s Disease

机译：声学和语言分析评估早期发作和遗传遗传症的疾病

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The PSEN1-E280A or Paisa mutation is responsible for most of Early-Onset Alzheimer’s (EOA) disease cases in Colombia. It affects a large kindred of over 5000 members that present the same phenotype. The most common symptoms are related to language disorders, where speech fluency is also affected due to the difficulty to access semantic information intentionally. This study proposes the use of acoustic and linguistic methods to extract features from speech recordings and their transcriptions to discriminate people with conditions related to the Paisa mutation. We consider state-of-the-art word-embedding methods like Word2Vec and Bidirectional Encoder Representations from Transformer to process the transcripts. The speech signals are modeled by using traditional acoustic features and speaker embeddings. To the best of our knowledge, this is the first study focused on evaluating genetic Alzheimer’s and EOA using acoustics and linguistics.
机译：PSEN1-E280A或PAISA突变对哥伦比亚的大部分早期阿尔茨海默氏症（EOA）病例负责。 它会影响超过5000多种呈现相同表型的巨大痕迹。 最常见的症状与语言障碍有关，其中语音流畅性也受到由于难以故意访问语义信息而受到影响。 本研究提出了使用声学和语言方法来提取语音记录及其转录的特征，以区分具有与Paisa突变有关的病症的人。 我们考虑最先进的单词嵌入方法，如来自变压器的Word2Vec和双向编码器表示来处理转录物。 语音信号是通过使用传统的声学特征和扬声器嵌入而建模的。 据我们所知，这是第一项研究专注于使用声学和语言学评估遗传阿尔茨海默和EOA的研究。

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