标题：Ten Years of Research on Automatic Voice and Speech Analysis of People With Alzheimer's Disease and Mild Cognitive Impairment: A Systematic Review Article
摘要：Background: In the last ten years, the field of voice and speech analysis has become increasingly popular, and numerous articles pointing to its usefulness on detecting neurodegenerative diseases have proliferated. Many studies have identified characteristic speech features that can be used to draw an accurate distinction between healthy ageing older people and those with mild cognitive impairment, and Alzheimer’s disease. Automatic speech analysis has been pointed out as an economical and reliable method for detecting the presence of both conditions. In this paper, a systematic review was conducted to determine which features are those and what is their diagnostic accuracy. Methods: peer-reviewed literature was searched across multiple databases. Studies that apply new procedures of automatic speech analysis to collect behavioral evidence of linguistic impairments along with their diagnostic accuracy on Alzheimer’s disease and mild cognitive impairment were included. Risk of bias was assessed by using JBI and QUADAS-2 checklists. Results: 35 citations met the inclusion criteria. Of these, 11 were descriptive studies that either identifed voice features or explored their cognitive correlates, and the rest were diagnostic studies. Overall, the assessed studies were of good quality and presented solid evidence of the usefulness of this technique. The distinctive acoustic and rhythmic features found are gathered. Most studies get a diagnosis accuracy over 88% for Alzheimer’s and 80% for Mild Cognitive Impairment. Conclusion: Automatic speech analysis is a promising tool for diagnosing Mild Cognitive Impairment and Alzheimer's disease. The reported features seem to be indicators of the cognitive changes of older people. The specific features and the cognitive changes involved could be the subject of further research.
关键词：Alzheimer' s disease; Mild Cognitive Impairment; Speech analysis; Language impairment; speech impairment
