![]() ![]() The potential for using speech as a biomarker for AD is based on several prospective values, including: 1) the ease with which speech can be recorded and tracked over time, 2) its non-invasiveness, 3) the fact that technologies for speech analysis have improved markedly in the past decade, boosted by advances in artificial intelligence (AI) and machine learning, and 4) the fact that speech problems may be manifest at different stages of the disease, making it a life-course assessment that has value unlimited by disease stage. Consequently, and due to the ubiquitous nature of speech and language, multiple studies rely on these modalities as sources of clinical information for AD, from foundational qualitative research (e.g., ) to more recent work on computational speech technology (e.g., ). Although memory loss is often considered the signature symptom of AD, language impairment may also appear in its early stages. Given its prevalence, it has effects beyond just patients and carers as it also has a severe societal and economic impact worldwide. It is the most common etiology of dementia. In such an emerging and heterogeneous field, shared tasks and data availability are important progression avenues.Īlzheimer’s disease (AD) is a neurodegenerative disease that involves decline of cognitive and functional abilities as the illness progresses. , one of the studies working on the Pitt Corpus, has released their subset as part of a challenge for INTERSPEECH 2020, providing the research community with a dataset matched for age and gender and with enhanced audio. , mentions that data are available upon request to authors. , who made available their identifiers for the CCC dataset. However, only share the exact specification of the subset of Pitt Corpus used for their analysis, in order for other researchers to be able to replicate their findings, taking advantage of the availability of the corpus. From the remaining 12 studies, nine use data from DementiaBank ( Pitt Corpus or Mandarin_Lu) and do report data origin and availability. The majority (77%, 39 studies) fail to report on data availability. Strikingly, very few studies make their data available, or even report on its (un)availability, even when using available data hosted by a different institution (e.g., studies using the Pitt Corpus). ![]()
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