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Semantic fluency is a commonly used task in psychology that provides data about executive function and semantic memory. Performance on the task is affected by conditions ranging from depression to dementia. The task involves participants naming as many members of a given category (e.g. animals) as possible in sixty seconds. Most of the analyses reported in the literature only rely on word counts and transcribed data, and do not take into account the evidence of utterance planning present in the speech signal. Using data from Korean, we show how prosodic analyses can be combined with computational linguistic analyses of the words produced to provide further insights into the processes involved in producing fluency data. We compare our analyses to an established analysis method for semantic fluency data, manual determination of lexically coherent clusters of words.
|Title of host publication||Interspeech 2016|
|Place of Publication||San Francisco, United States|
|Number of pages||5|
|Publication status||Published - 12 Sep 2016|
|Event||Interspeech 2016 - San Francisco, United States|
Duration: 8 Sep 2016 → 12 Sep 2016
|Publisher||International Speech Communication Association|
|Period||8/09/16 → 12/09/16|
- verbal fluency
- semantic fluency
- executive functions
- word embeddings
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