Determinism in speech pitch relation to emotion

Mahmoud, Ahmed Mustafa; Hassan, Wan Haslina

doi:10.1145/1655925.1655931

Cited by 3 publications

(1 citation statement)

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“…The success for the five classes was 81%. A description of the five emotional states (pleasure, sadness, fear, anger, and neutral state) is undertaken in (Mahmoud and Hassan, 2009). Here, the algorithm is based on the relationship of a height note versus the 12 half tones of the melodic scale.…”

Section: Introductionmentioning

confidence: 99%

Self-Organizing Maps as Data Classifiers in Medical Applications

Tuckova¹,

Bártů²,

Zetocha³

et al. 2011

Proceedings of the International Conference on Neural Computation Theory and Applications

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Many researchers use mathematical-engineering methods in different domains of life, and medical research is no exception. One area for application of such methods is to assist people with different forms of disabilities. The methods described in the following text are oriented towards the analysis of disordered children's speech with the diagnosis of Specific Language Impairment (SLI), also named as Developmental Dysphasia (DD), and the analysis of the expressive speech. Both methods make use of Kohonen Self-Organizing Maps (KSOM) or Supervised Self-Organizing Maps (SSOM) for the analysis and the classification of features from utterances of healthy and ill children, or adult speakers for emotions analysis. The possibility of cluster visualisation is used for monitoring of disorder trends and therapy success. These experiments also demonstrate the ability of the KSOM or SSOM to classify emotions.

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Section: Introductionmentioning

confidence: 99%