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arXiv · 1704.02046

End to End Deep Neural Network Frequency Demodulation of Speech Signals

Dan Elbaz·Michael Zibulevsky
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Abstract

Frequency modulation (FM) is a form of radio broadcasting which is widely used nowadays and has been for almost a century. We suggest a software-defined-radio (SDR) receiver for FM demodulation that adopts an end-to-end learning based approach and utilizes the prior information of transmitted speech message in the demodulation process. The receiver detects and enhances speech from the in-phase and quadrature components of its base band version. The new system yields high performance detection for both acoustical disturbances, and communication channel noise and is foreseen to out-perform the established methods for low signal to noise ratio (SNR) conditions in both mean square error and in perceptual evaluation of speech quality score.

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Dan Elbaz, Michael Zibulevsky. 2017-04-06. End to End Deep Neural Network Frequency Demodulation of Speech Signals. https://arxiv.org/abs/1704.02046

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