<?xml version='1.0' encoding='utf-8'?>
<eprints xmlns='http://eprints.org/ep2/data/2.0'>
  <eprint id='https://researchdata.bath.ac.uk/id/eprint/1150'>
    <eprintid>1150</eprintid>
    <rev_number>22</rev_number>
    <documents>
      <document id='https://researchdata.bath.ac.uk/id/document/16044'>
        <docid>16044</docid>
        <rev_number>2</rev_number>
        <files>
          <file id='https://researchdata.bath.ac.uk/id/file/53265'>
            <fileid>53265</fileid>
            <datasetid>document</datasetid>
            <objectid>16044</objectid>
            <filename>Jeremy-Leach-thesis-WAV-files.zip</filename>
            <mime_type>application/zip</mime_type>
            <hash>005dbaedf3191ce5e964695ba772e2d9</hash>
            <hash_type>MD5</hash_type>
            <filesize>56085450</filesize>
            <mtime>2022-05-27 10:57:07</mtime>
            <url>https://researchdata.bath.ac.uk/1150/1/Jeremy-Leach-thesis-WAV-files.zip</url>
          </file>
        </files>
        <eprintid>1150</eprintid>
        <pos>1</pos>
        <placement>1</placement>
        <mime_type>application/zip</mime_type>
        <format>other</format>
        <language>en</language>
        <security>public</security>
        <license>all_rights_reserved</license>
        <main>Jeremy-Leach-thesis-WAV-files.zip</main>
        <content>data</content>
      </document>
    </documents>
    <eprint_status>archive</eprint_status>
    <userid>1166</userid>
    <dir>disk0/00/00/11/50</dir>
    <datestamp>2022-05-27 14:26:30</datestamp>
    <lastmod>2024-06-14 14:01:46</lastmod>
    <status_changed>2022-05-27 14:26:30</status_changed>
    <type>data_collection</type>
    <metadata_visibility>show</metadata_visibility>
    <creators>
      <item>
        <name>
          <family>Leach</family>
          <given>Jeremy L.</given>
        </name>
        <id>~J.L.Leach@bath.ac.uk</id>
        <affiliation>University of Bath</affiliation>
        <contact>FALSE</contact>
      </item>
    </creators>
    <title>Audio files for &quot;Algorithmic composition and musical form&quot;</title>
    <subjects>
      <item>FB0170</item>
    </subjects>
    <divisions>
      <item>dept_math_sci</item>
    </divisions>
    <keywords>Computer-generated music, Automatic composition</keywords>
    <abstract>This dataset consists of 14 audio tracks generated by the algorithmic composition systems described in the associated thesis.

The thesis proposes that certain simple intra-musical meanings are closely related to the role of repetition and variation in music, as well as Gestalt grouping principles, and are often what makes music interesting to listen to. It describes the development and evaluation of three algorithmic composition systems that attempt to impart a degree of ‘meaning’ in their output.</abstract>
    <date>1999</date>
    <publisher>University of Bath</publisher>
    <full_text_status>public</full_text_status>
    <corp_contributors>
      <item>
        <type>RightsHolder</type>
        <corpname>University of Bath</corpname>
      </item>
    </corp_contributors>
    <funding>
      <item>
        <funder_name>Self-funded</funder_name>
      </item>
    </funding>
    <collection_method>The methods by which the compositions were generated are documented in the associated thesis.</collection_method>
    <techinfo>The files are in Waveform Audio File (WAV) format.</techinfo>
    <methodurl>
      <item>https://researchportal.bath.ac.uk/en/studentTheses/41fa1ad4-9c10-4ab3-9730-358bc439ddce</item>
    </methodurl>
    <language>en</language>
    <version>1</version>
    <doi>10.15125/BATH-01150</doi>
    <related_resources>
      <item>
        <link>https://researchportal.bath.ac.uk/en/studentTheses/41fa1ad4-9c10-4ab3-9730-358bc439ddce</link>
        <type>thesis</type>
      </item>
    </related_resources>
    <resourcetype>
      <general>Sound</general>
      <specific>Music</specific>
    </resourcetype>
  </eprint>
</eprints>
