3 research outputs found

    Speech Processing Approach for Diagnosing Dementia in an Early Stage

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    The clinical diagnosis of Alzheimer’s disease and other dementias is very challenging, especially in the early stages. Our hypothesis is that any disease that affects particular brain regions involved in speech production and processing will also leave detectable finger prints in the speech. Computerized analysis of speech signals and computational linguistics have progressed to the point where an automatic speech analysis system is a promising approach for a low-cost non-invasive diagnostic tool for early detection of Alzheimer’s disease.We present empirical evidence that strong discrimination between subjects with a diagnosis of probable Alzheimer’s versus matched normal controls can be achieved with a combination of acoustic features from speech, linguistic features extracted from an automatically determined transcription of the speech including punctuation, and results of a mini mental state exam (MMSE). We also show that discrimination is nearly as strong even if the MMSE is not used, which implies that a fully automated system is feasible. Since commercial automatic speech recognition (ASR) tools were unable to provide transcripts for about half of our speech samples, a customized ASR system was developed

    Comparison of different feature sets for identification of variants in progressive aphasia

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    The Genitive Ratio and its Applications

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    The genitive ratio (GR) is a novel method of classifying nouns as animate, concrete or abstract. English has two genitive (possessive) constructions: possessive-s (the boy's head) and possessive-of (the head of the boy). There is compelling evidence that preference for possessive-s is strongly influenced by the possessor's animacy. A corpus analysis that counts each genitive construction in three conditions (definite, indefinite and no article) confirms that occurrences of possessive-s decline as the animacy hierarchy progresses from animate through concrete to abstract. A computer program (Animyser) is developed to obtain results-counts from phrase-searches of Wikipedia that provide multiple genitive ratios for any target noun. Key ratios are identified and algorithms developed, with specific applications achieving classification accuracies of over 80%. The algorithms, based on logistic regression, produce a score of relative animacy that can be applied to individual nouns or to texts. The genitive ratio is a tool with potential applications in any research domain where the relative animacy of language might be significant. Three such applications exemplify that. Combining GR analysis with other factors might enhance established co-reference (anaphora) resolution algorithms. In sentences formed from pairings of animate with concrete or abstract nouns, the animate noun is usually salient, more likely to be the grammatical subject or thematic agent, and to co-refer with a succeeding pronoun or noun-phrase. Two experiments, online sentence production and corpus-based, demonstrate that the GR algorithm reliably predicts the salient noun. Replication of the online experiment in Italian suggests that the GR might be applied to other languages by using English as a 'bridge'. In a mental health context, studies have indicated that Alzheimer's patients' language becomes progressively more concrete; depressed patients' language more abstract. Analysis of sample texts suggests that the GR might monitor the prognosis of both illnesses, facilitating timely clinical interventions
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