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Abstract
Media authentication relies on the detection of inconsistencies that may indicate malicious editing in audio and video files. Traditionally, authentication processes are performed by forensics professionals using dedicated tools. There is rich research on the automation of this procedure, but the results do not yet guarantee the feasibility of providing automated tools. In the current approach, a computer-supported toolbox is presented, providing online functionality for assisting technically inexperienced users (journalists or the public) to investigate visually the consistency of audio streams. Several algorithms based on previous research have been incorporated on the backend of the proposed system, including a novel CNN model that performs a Signal-to-Reverberation-Ratio (SRR) estimation with a mean square error of 2.9%. The user can access the web application online through a web browser. After providing an audio/video file or a YouTube link, the application returns as output a set of interactive visualizations that can allow the user to investigate the authenticity of the file. The visualizations are generated based on the outcomes of Digital Signal Processing and Machine Learning models. The files are stored in a database, along with their analysis results and annotation. Following a crowdsourcing methodology, users are allowed to contribute by annotating files from the dataset concerning their authenticity. The evaluation version of the web application is publicly available online.
Highlights
News authentication is considered a vital task for reliable informational services
An AudioVisual Authentication application is presented, part of the Media Authentication Education (MAthE) project on computer-aided support of journalists and simple users against misinformation. It specializes in the authentication of audiovisual content in an audio-driven technical approach
It has the form of a web application and implements the functionality of a framework that promotes machine-assisted, human-centered decision making, collective intelligence, and collaboration in the battle against the malicious tampering of audiovisual content
Summary
Received: 7 January 2022News authentication is considered a vital task for reliable informational services. With the advancement of Information and Communication Technologies and the availability of easy-to-use editing and processing tools, one unwanted side-effect is the falsification of multimedia assets (i.e., images, audio, video) to alter the presented stories, making them more appealing (or intentionally doctored). In this context, unimodal solutions have been implemented to inspect each of the individual media entities, while multimodal forensic services are deployed through online collaborative environments, plug-ins, serious games, and gamification components [1,2,4,5].
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