Wydawnictwa Uczelniane / TUL Press

Stały URI zbioruhttp://hdl.handle.net/11652/17

Przeglądaj

Filtry

20232

Ustawienia

Autorsearch.filters.applied.operator.equals: search.filters.author.Kapusta, PawełTematsearch.filters.applied.operator.equals: search.filters.subject.artificial intelligence

Wyniki wyszukiwania

Teraz wyświetlane 1 - 2 z 2
  • Pozycja
    Predictive User Interface for Emerging Experiences
    (Wydawnictwo Politechniki Łódzkiej, 2023) Kapusta, Paweł; Duch, Piotr
    This research paper focuses on the use of predictive techniques to improve interaction with user interfaces in emerging experiences such as Virtual Reality, Augmented Reality, Metaverse, and touchless kiosks and dashboards. We propose the concept of intelligent snapping, which uses gaze tracking, head-pose tracking, hand tracking, as well as gesture recognition and hand posture recognition to catch the intent of the person rather than the actual input.
  • Pozycja
    A Convolutional and Recurrent Neural Network-based Approach for Speech Emotion Recognition
    (Wydawnictwo Politechniki Łódzkiej, 2023) Duch, Piotr; Wiatrowska, Izabela; Kapusta, Paweł
    Speech emotion recognition (SER) is a crucial aspect of humancomputer interaction. In this article, we propose a deep learning approach, using CNN and RNN architectures, for SER using both convolutional and recurrent neural networks. We evaluated the approach on four audio datasets, including CREMA-D, RAVDESS, TESS, and EMOVO. Our experiments tested various feature sets and extraction settings to determine optimal features for SER. Our results demonstrate that the proposed approach achieves high accuracy rates and outperforms state-of-the-art algorithms.