LipsID Using 3D Convolutional Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952608" target="_blank" >RIV/49777513:23520/18:43952608 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-99579-3_22" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-99579-3_22</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-99579-3_22" target="_blank" >10.1007/978-3-319-99579-3_22</a>
Alternative languages
Result language
angličtina
Original language name
LipsID Using 3D Convolutional Neural Networks
Original language description
This paper presents a proposition for a method inspired by iVectors for improvement of visual speech recognition in the similar way iVectors are used to improve the recognition rate of audio speech recognition. A neural network for feature extraction is presented with training parameters and evaluation. The network is trained as a classifier for a closed set of 64 speakers from the UWB-HSCAVC dataset and then the last softmax fully connected layer is removed to gain a feature vector of size 256. The network is provided with sequences of 15 frames and outputs the softmax classification to 64 classes. The training data consists of approximately 20000 sequences of grayscale images from the first 50 sentences that are common to every speaker. The network is then evaluated on the 60000 sequences created from 150 sentences from each speaker. The testing sentences are different for each speaker.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Speech and Computer 20th International Conference, SPECOM 2018 Leipzig, Germany, September 18–22, 2018, Proceedings
ISBN
978-3-319-99578-6
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
6
Pages from-to
209-214
Publisher name
Springer Nature Switzerland AG
Place of publication
Cham
Event location
Leipzig, Germany
Event date
Sep 18, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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