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journal.pcbi.1009707.pdf | 3.85 MB | Adobe PDF | 見る/開く |
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DCフィールド | 値 | 言語 |
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dc.contributor.author | Morita, Takashi | en |
dc.contributor.author | Koda, Hiroki | en |
dc.contributor.author | Okanoya, Kazuo | en |
dc.contributor.author | Tachibana, Ryosuke O. | en |
dc.contributor.alternative | 森田, 尭 | ja |
dc.contributor.alternative | 香田, 啓貴 | ja |
dc.contributor.alternative | 岡ノ谷, 一夫 | ja |
dc.contributor.alternative | 橘, 亮輔 | ja |
dc.date.accessioned | 2022-10-04T01:51:20Z | - |
dc.date.available | 2022-10-04T01:51:20Z | - |
dc.date.issued | 2021-12 | - |
dc.identifier.uri | http://hdl.handle.net/2433/276543 | - |
dc.description.abstract | Context dependency is a key feature in sequential structures of human language, which requires reference between words far apart in the produced sequence. Assessing how long the past context has an effect on the current status provides crucial information to understand the mechanism for complex sequential behaviors. Birdsongs serve as a representative model for studying the context dependency in sequential signals produced by non-human animals, while previous reports were upper-bounded by methodological limitations. Here, we newly estimated the context dependency in birdsongs in a more scalable way using a modern neural-network-based language model whose accessible context length is sufficiently long. The detected context dependency was beyond the order of traditional Markovian models of birdsong, but was consistent with previous experimental investigations. We also studied the relation between the assumed/auto-detected vocabulary size of birdsong (i.e., fine- vs. coarse-grained syllable classifications) and the context dependency. It turned out that the larger vocabulary (or the more fine-grained classification) is assumed, the shorter context dependency is detected. | en |
dc.language.iso | eng | - |
dc.publisher | Public Library of Science (PLoS) | en |
dc.rights | © 2021 Morita et al. | en |
dc.rights | This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | Syllables | en |
dc.subject | Finches | en |
dc.subject | Birds | en |
dc.subject | Language | en |
dc.subject | Zebra finch | en |
dc.subject | Acoustics | en |
dc.subject | Bird song | en |
dc.subject | Syntax | en |
dc.title | Measuring context dependency in birdsong using artificial neural networks | en |
dc.type | journal article | - |
dc.type.niitype | Journal Article | - |
dc.identifier.jtitle | PLOS Computational Biology | en |
dc.identifier.volume | 17 | - |
dc.identifier.issue | 12 | - |
dc.relation.doi | 10.1371/journal.pcbi.1009707 | - |
dc.textversion | publisher | - |
dc.identifier.artnum | e1009707 | - |
dc.identifier.pmid | 34962915 | - |
dcterms.accessRights | open access | - |
datacite.awardNumber | 17H06380 | - |
datacite.awardNumber | 19KT0023 | - |
datacite.awardNumber | 21H03781 | - |
datacite.awardNumber | 21K17805 | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/ja/grant/KAKENHI-PLANNED-17H06380/ | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-19KT0023/ | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-21H03781/ | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-21K17805/ | - |
dc.identifier.pissn | 1553-734X | - |
dc.identifier.eissn | 1553-7358 | - |
jpcoar.funderName | 日本学術振興会 | ja |
jpcoar.funderName | 日本学術振興会 | ja |
jpcoar.funderName | 日本学術振興会 | ja |
jpcoar.funderName | 日本学術振興会 | ja |
jpcoar.awardTitle | 言語の下位機能の生物学的実現 | ja |
jpcoar.awardTitle | 鳴禽の鳴きかわしは社会結合を促進するか | ja |
jpcoar.awardTitle | 感覚運動学習の敏感期:鳴禽の歌学習をモデルとした神経科学的・生理学的研究 | ja |
jpcoar.awardTitle | 発声運動学習が音声認識学習に与える影響に関する計算言語学的研究 | ja |
出現コレクション: | 学術雑誌掲載論文等 |
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