Next Article in Journal
Secure SCADA-IoT Platform for Industrial Automation and Control: A Collaborative-Communication Designed Model
Previous Article in Journal
On the Joint Use of NMF and Classification for Overlapping Acoustic Event Detection
Open AccessProceedings

Transferable Deep Features for Keyword Spotting

CIL/IIT/NCSR “Demokritos”, GR-15310 Agia Paraskevi, Greece
School of Electrical and Computer Engineering, National Technical University of Athens, GR-15773 Athens, Greece
Author to whom correspondence should be addressed.
Presented at the International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM), Kos Island, Greece, 2 September 2017.
Proceedings 2018, 2(2), 89;
Published: 9 January 2018
Deep features, defined as the activations of hidden layers of a neural network, have given promising results applied to various vision tasks. In this paper, we explore the usefulness and transferability of deep features, applied in the context of the problem of keyword spotting (KWS). We use a state-of-the-art deep convolutional network to extract deep features. The optimal parameters concerning their application are subsequently studied: the impact of the choice of hidden layer, the impact of applying dimensionality reduction with a manifold learning technique, as well as the choice of dissimilarity measure used to retrieve relevant word images. Extensive numerical results show that deep features lead to state-of-the-art KWS performance, even when the test and training set come from different document collections.
Keywords: deep features; keyword spotting; manifold learning; transferable features deep features; keyword spotting; manifold learning; transferable features
MDPI and ACS Style

Retsinas, G.; Sfikas, G.; Gatos, B. Transferable Deep Features for Keyword Spotting. Proceedings 2018, 2, 89.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop