5833277
doi
10.5281/zenodo.5833277
oai:zenodo.org:5833277
user-marvel_project
user-eu
MARVEL - D4.1: Optimal audio-visual capturing, analysis and voice anonymisation – initial version
Elfi Fertl
IFAG
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
voice anonymisation
MEMS
audio-visual capturing
voice activity detection
smart cities
Edge-to-Fog-to-Cloud
<p>This report focuses on the initial version of the optimal audio-visual capturing, analysis and voice anonymisation. In the field of audio capturing, this document gives detailed information about the hardware developed and used in the scope of this project. Some consist of only the microphone and a simple connector, while others come with a processing unit that allows audio capturing via USB, streaming to a cloud via WiFi and even Edge AI processing. First versions of different data acquisition installations using the already available audio devices in different scenarios are presented, along with the first results of those experiments. This section concludes with information about plans for pre-processing for data analysis through the usage of Edge AI techniques. The second section of the document is about devAIce SDK, a modular technology optimised to work on cross-platforms and contains several AI models such as the Voice Activity Detection (VAD) tool as well as the feature extraction toolkit, openSMILE. It is used for audio analytics and sound event detection, acoustic scene classification and speech analysis which is a fundamental step to ensure privacy compliance and is designed to be implemented on high-end edge devices. Furthermore, an Android app used to record environmental acoustics and user annotations, SensMiner, is introduced.</p>
Zenodo
2022-01-10
info:eu-repo/semantics/report
5833276
user-marvel_project
user-eu
award_title=Multimodal Extreme Scale Data Analytics for Smart Cities Environments; award_number=957337; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/957337; funder_id=00k4n6c32; funder_name=European Commission;
1673948572.273581
2069449
md5:cc3dd6c9bebb4dc8dd228e4277baf082
https://zenodo.org/records/5833277/files/MARVEL-d4.1.pdf
public
10.5281/zenodo.5833276
isVersionOf
doi