A Framework for Adaptive Real-Time Loudness Control
Over the last few years, loudness control represents one of the most frequently investigated topics in audio signal processing. In this paper we describe a framework designed to provide adaptive real-time loudness measurement and processing of audio files and streamed content being reproduced by mobile players hosted in laptops, tablets, and mobile phones. The proposed method aims to improve the users’ listening experience by normalizing the loudness level of the content in real-time, while preserving the original creative intent of the original soundtrack. The loudness measurement and adaptation is based on a customization of the High Efficiency Loudness Model algorithm described in the AES Convention Paper #8612 (“HELM: High Efficiency Loudness Model for Broadcast Content,” presented at the 132nd Convention, April 2012). Technical and subjective tests were performed in order to evaluate the performance of the proposed method. In addition, the way the subjective test was arranged offered the opportunity to gather information on the preferred Target Level of streamed and media files reproduced on portable devices.
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