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International Journal of Speech Technology

Erschienen in:

07.04.2020

A probabilistic stochastic model for analysis on the epileptic syndrome using speech synthesis and state space representation

verfasst von: F. Anitha Florence Vinola, G. Padma

Erschienen in: International Journal of Speech Technology | Ausgabe 2/2020

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Abstract

A probabilistic stochastic model deals with the real life applications of networks such as wireless communication, signals, speech synthesis, biomedical data in terms of blood pressure, ECG, EEG and temperature of a human being etc. An important class of stochastic process is Markov process which possess the past forgetting property, that is the result arises from each incident rely on the present but not on the past. This Markov property enables reasoning and computation with the model that would be otherwise intractable. In this paper the speech disorder developed by the Febrile infection-related epilepsy syndrome (FIRES) disease whose symptoms are discussed using Markov chain modeling as a new technique and its properties using a pictorial representation to enable the identification of an effective speech disorder therapy.

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Titel: A probabilistic stochastic model for analysis on the epileptic syndrome using speech synthesis and state space representation
verfasst von: F. Anitha Florence Vinola
G. Padma
Publikationsdatum: 07.04.2020
Verlag: Springer US
Erschienen in: International Journal of Speech Technology / Ausgabe 2/2020
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI: https://doi.org/10.1007/s10772-020-09702-1

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