Enhancement by postfiltering for speech and audio coding in ad hoc sensor networks

Sneha Das,Tom Bäckström

doi:10.1121/10.0003208

Abstract

Enhancement algorithms for wireless acoustic sensor networks (WASNs) are indispensable with the increasing availability and usage of connected devices with microphones. Conventional spatial filtering approaches for enhancement in WASNs approximate quantization noise with an additive Gaussian distribution, which limits performance due to the non-linear nature of quantization noise at lower bitrates. This work proposes a postfilter for enhancement based on Bayesian statistics to obtain a multidevice signal estimate, which explicitly models the quantization noise. The experiments using perceptual signal-to-noise ratio, perceptual evaluation of speech quality, and MUSHRA (multistimulus with hidden reference and anchors) scores demonstrate that the proposed postfilter can be used to enhance signal quality in ad hoc sensor networks.

Highlights

The emergence of connected and portable devices like smartphones and the rising popularity of voice user-interfaces and devices equipped with microphones enable the necessary infrastructure for ad hoc wireless acoustic sensor networks (WASNs)
The dense, ad hoc positioning and collaboration in a WASN leads to efficient sampling of the acoustic space, thereby gaining higher quality signal estimates compared to single-channel estimates (Bertrand, 2011)
We propose a Bayesian postfilter for enhancement in ad hoc WASNs, which explicitly models the quantization noise within the optimization framework of the filter and can be applied on top of existing codecs with minimal modifications

Summary

Introduction

The emergence of connected and portable devices like smartphones and the rising popularity of voice user-interfaces and devices equipped with microphones enable the necessary infrastructure for ad hoc wireless acoustic sensor networks (WASNs). Typical applications of ad hoc WASNs use microphones on low-resource devices, such that we need low-complexity methods that use bandwidth efficiently to compress and transmit the acoustic signals. This involves quantization at the encoder, whereby the received signal at the decoder is usually degraded by quantization noise (B€ackstr€om and Fischer, 2016; B€ackstr€om and Fischer, 2017; B€ackstr€om, 2017; Dragotti and Gastpar, 2009; Pradhan and Ramchandran, 2003). A study on rate-constrained optimal beamforming showed the advantage of using spatially separated microphones in HAs, the method assumes that the joint statistics of signals are available at the processing nodes (Roy and Vetterli, 2008). Their performance in single-channel mode can not compete with conventional single-channel codecs

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