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		<updated>2026-04-18T12:49:18Z</updated>
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				<updated>2021-02-03T15:59:43Z</updated>
		
		<summary type="html">&lt;p&gt;Scipediacontent moved page &lt;a href=&quot;/public/Draft_Content_501099957&quot; class=&quot;mw-redirect&quot; title=&quot;Draft Content 501099957&quot;&gt;Draft Content 501099957&lt;/a&gt; to &lt;a href=&quot;/public/Trivedi_et_al_2012a&quot; title=&quot;Trivedi et al 2012a&quot;&gt;Trivedi et al 2012a&lt;/a&gt;&lt;/p&gt;
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				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;Revision as of 15:59, 3 February 2021&lt;/td&gt;
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		<author><name>Scipediacontent</name></author>	</entry>

	<entry>
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		<title>Scipediacontent: Created page with &quot; == Abstract ==   part of human-centered driver assist framework for holistic multimodal sensing, we present an evaluation of independent vector analysis for speaker recogniti...&quot;</title>
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				<updated>2021-02-03T15:59:41Z</updated>
		
		<summary type="html">&lt;p&gt;Created page with &amp;quot; == Abstract ==   part of human-centered driver assist framework for holistic multimodal sensing, we present an evaluation of independent vector analysis for speaker recogniti...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
 part of human-centered driver assist framework for holistic multimodal sensing, we present an evaluation of independent vector analysis for speaker recognition task inside an automotive vehicle. Independent component analysis-based blind source separation algorithms have attracted attentions in recent years in the application of speech separation and enhancement. Compared to the traditional beamforming technique, the blind source separation method may typically require less number of microphones and perform better under reverberant environment. We recorded two speakers in the driver and front-passenger seats talking simultaneously inside a car and used independent vector analysis to separate the two speech signals. In the speaker recognition task, we show that by training the model with the speech signals from the IVA process, our system is able to achieve 95 % accuracy from a 1-second speech segment.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Original document ==&lt;br /&gt;
&lt;br /&gt;
The different versions of the original document can be found in:&lt;br /&gt;
&lt;br /&gt;
* [http://cvrr.ucsd.edu/publications/2012/Yamada_ITSC2012.pdf http://cvrr.ucsd.edu/publications/2012/Yamada_ITSC2012.pdf]&lt;br /&gt;
&lt;br /&gt;
* [https://zenodo.org/record/1274700 https://zenodo.org/record/1274700]&lt;br /&gt;
&lt;br /&gt;
* [http://cvrr.ucsd.edu/publications/2012/Yamada_ITSC2012.pdf http://cvrr.ucsd.edu/publications/2012/Yamada_ITSC2012.pdf],&lt;br /&gt;
: [http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000006338907 http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000006338907],&lt;br /&gt;
: [https://dblp.uni-trier.de/db/conf/itsc/itsc2012.html#YamadaTT12 https://dblp.uni-trier.de/db/conf/itsc/itsc2012.html#YamadaTT12],&lt;br /&gt;
: [https://academic.microsoft.com/#/detail/2014857913 https://academic.microsoft.com/#/detail/2014857913]&lt;br /&gt;
&lt;br /&gt;
* [http://xplorestaging.ieee.org/ielx5/6328848/6338591/06338907.pdf?arnumber=6338907 http://xplorestaging.ieee.org/ielx5/6328848/6338591/06338907.pdf?arnumber=6338907],&lt;br /&gt;
: [http://dx.doi.org/10.1109/itsc.2012.6338907 http://dx.doi.org/10.1109/itsc.2012.6338907]&lt;/div&gt;</summary>
		<author><name>Scipediacontent</name></author>	</entry>

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