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    xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd"
    xmlns="http://www.loc.gov/MARC21/slim">

  <leader>02418caa a2200229   4500</leader>
  <controlfield tag="008">210629s9999    xx            000 0 und d</controlfield>
  <datafield tag="022" ind1=" " ind2=" ">
    <subfield code="a">2083-389X</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="a">Animesh Barman</subfield>
  </datafield>
  <datafield tag="245" ind1=" " ind2="0">
    <subfield code="a">DEVELOPMENT AND STANDARDIZATION OF AUDITORY LOW-FREQUENCY WORD LISTS IN HINDI</subfield>
  </datafield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="c">2016</subfield>
  </datafield>
  <datafield tag="300" ind1=" " ind2=" ">
    <subfield code="a">39&#x2013;49</subfield>
  </datafield>
  <datafield tag="490" ind1=" " ind2=" ">
    <subfield code="v">Volume 6 Issue 4</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">Background: Conventionally, it is believed that high-frequency auditory information is important for speech understanding. This is only partly true, as recent studies have demonstrated the importance of low-frequency information. This research was taken up to develop, standardize, and validate auditory low-frequency word lists in Hindi, an Indian language. Material and Methods: The first phase of the study involved collection of bisyllabic words followed by verification by a native linguist. Words were then short-listed based on familiarity ratings given by 10 adult native speakers; those words were recorded and the best recorded words selected through subjective and objective analysis. Then, using Fast Fourier Transform and k-means clustering, words with more energy below 1.5 kHz were isolated. Finally, equally difficult 10 word lists were generated by obtaining psychometric function curves. Finally, lists were administered on 40 adult normal hearing particip Results:Results showed a similar trend of increase in speech identification scores with increase in SL across all lists except list 4. During the final phase, developed lists were validated on 10 simulated low-frequency cochlear hearing loss participants. Hearing loss was simulated using Matlab and National Institute for Occupational Safety and Health (NIOSH) software. Results of validation revealed that auditory low-frequency word lists were sensitive enough to tap the speech understanding difficulty in the simulated condition. Conclusions: The developed word lists can be used clinically to assess communication ability in individuals with rising hearing loss. The word lists also have the potential to assess the performance after amplification provided to individuals with rising hearing loss.</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Mahima Gupta</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Niraj Kumar Singh</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Prashanth Prabhu</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Spoorthi Thammaiah</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Vijaya Kumar Narne</subfield>
  </datafield>
  <datafield tag="773" ind1=" " ind2=" ">
    <subfield code="a">Journal of Hearing Science, </subfield>
  </datafield>
  <datafield tag="856" ind1=" " ind2=" ">
    <subfield code="u">https://doi.org/10.17430/899781</subfield>
  </datafield>
  <datafield tag="942" ind1=" " ind2=" ">
    <subfield code="c">FJAS</subfield>
    <subfield code="y">FJAS</subfield>
  </datafield>
  <datafield tag="999" ind1=" " ind2=" ">
    <subfield code="c">18002</subfield>
    <subfield code="d">18002</subfield>
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