English speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive Parameter Elimination. The feature extraction process is explained, applied feature selection methods are presented and obtained results are discussed
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1007/978-3-319-98677-4
- Category
- Aktywność konferencyjna
- Type
- materiały konferencyjne indeksowane w Web of Science
- Language
- angielski
- Publication year
- 2018
