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        <identifier>oai:figshare.com:article/33348912</identifier>
        <datestamp>2026-09-22T09:21:34Z</datestamp>
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          <dc:title>Supporting data for "Phonetic substance in phonological learning"</dc:title>
          <dc:creator>Shuang Zheng (12989453)</dc:creator>
          <dc:creator>Youngah Do (9057116)</dc:creator>
          <dc:subject>Linguistic structures (incl. phonology, morphology and syntax)</dc:subject>
          <dc:subject>phonological learning</dc:subject>
          <dc:subject>learning biases</dc:subject>
          <dc:subject>vowel harmony</dc:subject>
          <dc:subject>neural network modeling</dc:subject>
          <dc:subject>artificial language learning</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;This dataset contains all data generated and collected in my thesis research.&lt;/p&gt;&lt;p dir="ltr"&gt;Feature Model contains simulation results from a text-based sequence-to-sequence neural network trained on artificial vowel harmony and vowel disharmony datasets with phonological feature initializations. Reported in Chapter 3 of “Phonetic substance in phonological learning.”&lt;/p&gt;&lt;p dir="ltr"&gt;Segment Model contains simulation results from a text-based sequence-to-sequence neural network trained on artificial vowel harmony and vowel disharmony datasets without any featural specifications. Reported in Chapter 3 of “Phonetic substance in phonological learning.”&lt;br&gt;&lt;br&gt;Acoustic Model contains simulation results from a speech-based sequence-to-sequence neural network trained on artificial vowel harmony and vowel disharmony datasets. Reported in Chapter 4 of “Phonetic substance in phonological learning.”&lt;br&gt;&lt;br&gt;Behavioral Experiment contains behavioral data collected from an artificial language learning study on vowel harmony and vowel disharmony with varying generalization consistency. Reported in Chapter 5 of “Phonetic substance in phonological learning.”&lt;br&gt;&lt;br&gt;Interaction Model contains simulation results from a speech-based sequence-to-sequence neural network trained on artificial vowel harmony and vowel disharmony datasets differing in phonological conditioning contexts. Reported in Chapter 5 of “Phonetic substance in phonological learning.”&lt;/p&gt;</dc:description>
          <dc:date>2026-09-22T09:21:34Z</dc:date>
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          <dc:identifier>10.25442/hku.33348912.v1</dc:identifier>
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