Система голосового управління робототехнікою в шумовому середовищі
DOI:
https://doi.org/10.18372/1990-5548.81.19016Ключові слова:
мовні сигнали, голосове управління, адаптивна вейвлет-фільтрація, мел-частотні кепстральні коефіцієнти, суміші Гаусових розподілів, метод опорних векторів, канал зв’язку, коефіцієнт нелінійних спотвореньАнотація
У роботі проведено аналіз ефективності розробленої системи голосового управління робототехнікою на основі MFCC і GMM-SVM в умовах впливу завад у каналі зв’язку. Система дає змогу характеризувати індивідуальні особливості мовних сигналів із подальшою їхньою класифікацією та ухваленням достовірного рішення щодо інтерпретації та виконання голосових команд роботизованою технікою. Запропоновану систему голосового управління робототехнікою на основі MFCC і GMM-SVM реалізовано за допомогою таких технологій: 1) виділення ділянок активної мови за допомогою розрахунку короткочасної енергії та кількості перетинів нуля між суміжними кадрами мовного сигналу; 2) адаптивна вейвлет-фільтрації мовного сигналу, де необхідно провести генерацію порогових значень, що дасть змогу зменшити вплив адитивного шуму; 3) виділення ознак розпізнавання, в якості яких використовуються мел-частотні кепстральні коефіцієнти; 4) класифікація ознак розпізнавання на основі сумішей Гауссових розподілів та методу опорних векторів з використанням лінійного ядра Кампбелла та методу головних компонент з проекцією на латентні структури, що забезпечить зменшення помилок 1-го та 2-го роду.
Посилання
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