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Authors: Lukas Mateju ; Petr Cerva and Jindrich Zdansky

Affiliation: Technical University of Liberec, Czech Republic

ISBN: 978-989-758-196-0

Keyword(s): Deep Neural Networks, Speech Activity Detection, Speech Recognition, Speech Transcription.

Related Ontology Subjects/Areas/Topics: Design and Implementation of Signal Processing Systems ; Multimedia ; Multimedia Signal Processing ; Multimedia Systems and Applications ; Neural Networks, Spiking Systems, Genetic Algorithms and Fuzzy Logic ; Telecommunications

Abstract: This paper deals with the task of Speech Activity Detection (SAD). Our goal is to develop a SAD module suitable for a system for broadcast data transcription. Various Deep Neural Networks (DNNs) are evaluated for this purpose. Training of DNNs is performed using speech and non-speech data as well as artificial data created by mixing of both these data types at a desired level of Signal-to-Noise Ratio (SNR). The output from each DNN is smoothed using a decoder based on Weighted Finite State Transducers (WFSTs). The presented experimental results show that the use of the resulting SAD module leads to a) a slight improvement in transcription accuracy and b) a significant reduction in the computation time needed for transcription.

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Paper citation in several formats:
Mateju, L.; Cerva, P. and Zdansky, J. (2016). Study on the Use of Deep Neural Networks for Speech Activity Detection in Broadcast Recordings.In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 5: SIGMAP, (ICETE 2016) ISBN 978-989-758-196-0, pages 45-51. DOI: 10.5220/0005952700450051

@conference{sigmap16,
author={Lukas Mateju. and Petr Cerva. and Jindrich Zdansky.},
title={Study on the Use of Deep Neural Networks for Speech Activity Detection in Broadcast Recordings},
booktitle={Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 5: SIGMAP, (ICETE 2016)},
year={2016},
pages={45-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005952700450051},
isbn={978-989-758-196-0},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 5: SIGMAP, (ICETE 2016)
TI - Study on the Use of Deep Neural Networks for Speech Activity Detection in Broadcast Recordings
SN - 978-989-758-196-0
AU - Mateju, L.
AU - Cerva, P.
AU - Zdansky, J.
PY - 2016
SP - 45
EP - 51
DO - 10.5220/0005952700450051

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