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Enhancement by postfiltering for speech and audio coding in ad hoc sensor networks
1Department of Signal Processing and Acoustics, Aalto University, 02230 Espoo, Finland sneha.das@aalto.fi, tom.backstrom@aalto.fi.
JASA Express Letters
|September 26, 2022
Summary
This study introduces a new postfilter for wireless acoustic sensor networks (WASNs). The Bayesian-based enhancement algorithm improves signal quality by accurately modeling quantization noise, outperforming conventional methods.
Area of Science:
- Signal Processing
- Acoustic Engineering
- Wireless Sensor Networks
Background:
- Wireless acoustic sensor networks (WASNs) are crucial for connected devices.
- Traditional enhancement methods struggle with non-linear quantization noise at low bitrates.
Purpose of the Study:
- To develop an advanced postfilter for WASN signal enhancement.
- To explicitly model quantization noise for improved performance.
Main Methods:
- Proposed a Bayesian statistics-based postfilter.
- Developed a multidevice signal estimation technique.
- Explicitly modeled quantization noise in the enhancement process.
Main Results:
- The proposed postfilter demonstrated significant signal quality enhancement.
- Achieved superior performance compared to conventional spatial filtering.
- Validated through perceptual signal-to-noise ratio, perceptual evaluation of speech quality, and MUSHRA scores.
Conclusions:
- The Bayesian postfilter effectively enhances signals in ad hoc WASNs.
- Accurate quantization noise modeling is key to improving low-bitrate audio enhancement.
- The proposed method offers a robust solution for practical WASN applications.
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