Since a cathode-ray tube television was introduced first to the consumers in the late 1920s, a variety of multimedia device form-factors has appeared in the consumer market until now. Although the values of multimedia devices had been mostly put on picture quality and sound quality in the past, it is undoubtedly told at this moment that user experience is the most important and attractive value for the multimedia products. As for now, almost all outstanding features of the brand-new products are the technologies about user convenience such as voice user interaction, device unlock, contents recommendation, and so on. Likewise, an unprecedented feature of smart TVs, the Active Voice Amplifier, was introduced in the Consumer Electronics Show 2020, and it detects disturbing noise and enhances voice clarity accordingly and automatically. To design this feature and make it work in real time on real devices, state-ofthe- art signal processing methods and deep learning technologies are integrated in a function for the novel approach of noisy environment detection and speech extraction from multimedia audio contents. This paper overviews what this function pursues in user experience, describes how it was designed in terms of signal processing methods, and demonstrates how effectively it works on real-time TV systems.
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