Estimating & Mitigating the Impact of Acoustic Environments on Machine-to-Machine Signalling

Amogh Matt; Dan Stowell

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arXiv · 1908.04672

Estimating & Mitigating the Impact of Acoustic Environments on Machine-to-Machine Signalling

Amogh Matt·Dan Stowell

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Abstract

The advance of technology for transmitting Data-over-Sound in various IoT and telecommunication applications has led to the concept of machine-to-machine over-the-air acoustic signalling. Reverberation can have a detrimental effect on such machine-to-machine signals while decoding. Various methods have been studied to combat the effects of reverberation in speech and audio signals, but it is not clear how well they generalise to other sound types. We look at extending these models to facilitate machine-to-machine acoustic signalling. This research investigates dereverberation techniques to shortlist a single-channel reverberation suppression method through a pilot test. In order to apply the chosen dereverberation method a novel method of estimating acoustic parameters governing reverberation is proposed. The performance of the final algorithm is evaluated on quality metrics as well as the performance of a real machine-to-machine decoder. We demonstrate a dramatic reduction in error rate for both audible and ultrasonic signals.

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BibTeX RIS

Amogh Matt, Dan Stowell. 2019-08-13. Estimating & Mitigating the Impact of Acoustic Environments on Machine-to-Machine Signalling. https://arxiv.org/abs/1908.04672

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