Detail publikace

Classification of Czech Sign Language Alphabet Diacritics via LSTM

ŠNAJDER, J. KREJSA, J.

Originální název

Classification of Czech Sign Language Alphabet Diacritics via LSTM

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The paper presents the classification of image sequences of the single-handed Czech sign language alphabet diacritics. Since diacritics are expressed by the motion of the hand, the classification is performed by the Long Short-Term Memory recurrent neural network. Annotation of the dataset is done by the MediaPipe framework, and the neural network is constructed with the TensorFlow computational library. The paper describes the proposed method's flow, data acquisition, preprocessing, and training. Obtained results consist of the validation dataset's classification success rate and testing on whole signed words and sentences. The overall success rate was around 88%.

Klíčová slova

Czech sign language; classification; MediaPipe; image sequence; Long Short-Term Memory

Autoři

ŠNAJDER, J.; KREJSA, J.

Vydáno

9. 12. 2022

Nakladatel

Institute of Electrical and Electronics Engineers Inc.

Místo

Pilsen

ISBN

978-1-6654-1039-7

Kniha

2022 20th International Conference on Mechatronics - Mechatronika (ME)

Edice

1st

Strany od

178

Strany do

182

Strany počet

5

URL

https://ieeexplore.ieee.org/document/9983436/

BibTex

@inproceedings{BUT182996,
  author="Jan {Šnajder} and Jiří {Krejsa}",
  title="Classification of Czech Sign Language Alphabet Diacritics via LSTM",
  booktitle="2022 20th International Conference on Mechatronics - Mechatronika (ME)",
  year="2022",
  series="1st",
  pages="178--182",
  publisher="Institute of Electrical and Electronics Engineers Inc.",
  address="Pilsen",
  doi="10.1109/ME54704.2022.9983436",
  isbn="978-1-6654-1039-7",
  url="https://ieeexplore.ieee.org/document/9983436/"
}