Sopon Phumeechanya. Temporal keyframe technique based on CNN and LSTM for enhancing lip reading performance. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2024.
Temporal keyframe technique based on CNN and LSTM for enhancing lip reading performance
Abstract:
The purpose of this research is to present a
method for improving lip reading performance through the
analysis of temporal keyframes using CNN and LSTM. The
performance of the model is determined by employing the input
data from the data preparation process. The lip image data is
divided into three groups for development: 3 frames, 5 frames,
and 10 frames, which include half-lip image data. Lip reading
research has never been conducted before based on the
assumption of a typical human body shape with left and right
symmetry, as in this study. When the unseen test set was
evaluated, 10 frames achieved the best recognition rate, with
results of 0.879% accuracy for the full lip image dataset and
0.868% accuracy for the half lip image dataset, exhibiting
comparable performance.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2024
Modified:
2025-01-23
Issued:
2025-01-23
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BibliograpyCitation :
In Rajamangala University of Technology Krungthep. 12th International Electrical Engineering Congress (iEECON 2024) (pp.276-280). Bangkok : Rajamangala University of Technology Krungthep