A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit <a rel="external noopener" href="https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/chhetri_icme2006.pdf">the original URL</a>. The file type is <code>application/pdf</code>.
Acoustic Echo Cancelation for High Noise Environments
<span title="">2006</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/pmefrmqsezb5zd3w7pf5k7fmxu" style="color: black;">2006 IEEE International Conference on Multimedia and Expo</a>
</i>
Preserved Fulltext
Acoustic echo cancellation (AEC) is highly imperative for enhanced communication in noisy environments such as a car or a conference room. In this work, we present a dualstructured AEC architecture that improves both the convergence time and misadjustment of a conventional adaptive subband AEC algorithm in high noise environments. In this architecture, one part performs smooth adaptation while the other part performs fast adaptation; a convergence detector is implemented to facilitate switching
<span class="external-identifiers">
<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icme.2006.262666">doi:10.1109/icme.2006.262666</a>
<a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icmcs/ChhetriSF06.html">dblp:conf/icmcs/ChhetriSF06</a>
<a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/trdzi6eehnaallion34dnza3zy">fatcat:trdzi6eehnaallion34dnza3zy</a>
</span>
more »
... between the fast and smooth adaptations. We propose the momentum normalized least mean square (MNLMS) algorithm for smooth adaptation and we implement the NLMS algorithm for fast adaptation. The current architecture provides up to 3-4 dB echo reduction improvement over a conventional adaptive subband AEC algorithm and it helps minimize near-end distortion and artifacts in the post-processed AEC output.
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200323045940/https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/chhetri_icme2006.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext">
<button class="ui simple right pointing dropdown compact black labeled icon button serp-button">
<i class="icon ia-icon"></i>
Web Archive
[PDF]
<div class="menu fulltext-thumbnail">
<img src="https://blobs.fatcat.wiki/thumbnail/pdf/d5/0f/d50f6b9a0497725de474647d0b680764cec37106.180px.jpg" alt="fulltext thumbnail" loading="lazy">
</div>
</button>
</a>
<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icme.2006.262666">
<button class="ui left aligned compact blue labeled icon button serp-button">
<i class="external alternate icon"></i>
ieee.com
</button>
</a>