Self-content-based audio inpainting

• A packet loss concealment approach capable of handling long audio gaps.
• Based on past audio-examples of the same speaker.
• Incorporates a statistical model.
• Method׳s performance is demonstrated using a large subjective listeners survey.

The popularity of voice over Internet protocol (VoIP) systems is continuously growing. Such systems depend on unreliable Internet communication, in which chunks of data often get lost during transmission. Various solutions to this problem were proposed, most of which are better suited to small rates of lost data. This work addresses this problem by filling in missing data using examples taken from prior recorded audio of the same user. Our approach also harnesses statistical priors and data inpainting smoothing techniques. The effectiveness of the proposed solution is demonstrated experimentally, even in large data-gaps, which cannot be handled by the standard packet loss concealment techniques.