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    <identifier>10.11922/sciencedb.o00114.00058</identifier>
    <datestamp>2021-12-10T15:30:00Z</datestamp>
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  <dc:date>2021-12-10</dc:date>
  <dc:title>Neural codec for natural language understanding</dc:title>
  <dc:identifier>doi:10.11922/sciencedb.o00114.00058</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>In recent years, distributed representation and codec technologies have been widely used in natural language processing. At the same time, they have also provided new approaches and paradigms for language cognitive computing research. So, how does the human brain represent language? How are the neural encoding and decoding performanced in different distributed representation methods? Can language information be reconstructed from neuroimaging data? This report will introduce part of the exploratory work that our team has carried out in recent years on those issues, and give preliminary prospects for the future development of this direction.</dc:description>
  <dc:subject>Distributed representation; language cognitive computing; CODEC</dc:subject>
  <dc:creator>ZONG Chengqing</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
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  <dc:publisher>Science Data Bank</dc:publisher>
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