ОЦІНКА ЯКОСТІ РОЗПІЗНАВАННЯ ГОЛОСОВИХ КОМАНД ЛЮДИНИ
Abstract
This work is devoted to assessing the field of artificial neural networks has grown rapidly in recent years. This has been accompanied by an insurgence of work in speech recognition. Most speech recognition research has centered on stochastic models, in particular the use of hidden Markov models (HMMs). Alternate techniques have focused on applying neural networks to classify speech signals. The inspiration for using neural networks as a classifier stems from the fact that neural networks within the human brain are used for speech recognition. This analogy unfortunately falls short of being close to an actual model of the brain, but the modeling mechanism and the training procedures allow the possiblility of using a neural network as a stochastic model that can be discrimitively trained.
Радіоелектроніка та молодь у XXI столітті. Т. 4 : Конференція "Перспективи розвитку інфокомунікацій та інформаційно-вимірювальних технологій": матеріали 28-го Міжнар. молодіж. форуму, 16–18 квіт. 2024 р.