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CITISEN A Deep Learning-Based Speech Signal-Processing Mobile Application

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Document pages: 9 pages

Abstract: In this paper, we present a deep learning-based speech signal-processingmobile application, CITISEN, which can perform three functions: speechenhancement (SE), acoustic scene conversion (ASC), and model adaptation (MA).For SE, CITISEN can effectively reduce noise components from speech signals andaccordingly enhance their clarity and intelligibility. For ASC, CITISEN canconvert the current background sound to a different background sound. Finally,for MA, CITISEN can effectively adapt an SE model, with a few audio files, whenit encounters unknown speakers or noise types; the adapted SE model is used toenhance the upcoming noisy utterances. Experimental results confirmed theeffectiveness of CITISEN in performing these three functions via objectiveevaluation and subjective listening tests. The promising results reveal thatthe developed CITISEN mobile application can potentially be used as a front-endprocessor for various speech-related services such as voice communication,assistive hearing devices, and virtual reality headsets.

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