{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00216629","sets":["1164:5159:10869:10870"]},"path":["10870"],"owner":"44499","recid":"216629","title":["頭蓋内脳波からのTransformer モデルによるテキストデコーディング"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-02-22"},"_buckets":{"deposit":"08bfb8f4-60cd-40d6-a744-e257823a6915"},"_deposit":{"id":"216629","pid":{"type":"depid","value":"216629","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"頭蓋内脳波からのTransformer モデルによるテキストデコーディング","author_link":["559389","559399","559397","559393","559394","559392","559385","559398","559387","559396","559395","559388","559391","559400","559390","559386"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"頭蓋内脳波からのTransformer モデルによるテキストデコーディング"},{"subitem_title":"Transformer-Based Text Decoding Using Electrocorticography","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ポスターセッション2","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-02-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京農工大学大学院工学府電子情報工学専攻"},{"subitem_text_value":"東京農工大学大学院工学府電子情報工学専攻"},{"subitem_text_value":"順天堂大学脳神経外科"},{"subitem_text_value":"順天堂大学脳神経外科"},{"subitem_text_value":"順天堂大学脳神経外科"},{"subitem_text_value":"順天堂大学脳神経外科"},{"subitem_text_value":"東京工業大学情報理工学院情報工学系"},{"subitem_text_value":"東京農工大学大学院工学府電子情報工学専攻"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Electronic and Information Engineering, Tokyo University of Agriculture and Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Electronic and Information Engineering, Tokyo University of Agriculture and Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Neurosurgery, Juntendo University","subitem_text_language":"en"},{"subitem_text_value":"Department of Neurosurgery, Juntendo University","subitem_text_language":"en"},{"subitem_text_value":"Department of Neurosurgery, Juntendo University","subitem_text_language":"en"},{"subitem_text_value":"Department of Neurosurgery, Juntendo University","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science, Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Electronic and Information Engineering, Tokyo University of Agriculture and Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/216629/files/IPSJ-SLP22140028.pdf","label":"IPSJ-SLP22140028.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLP22140028.pdf","filesize":[{"value":"2.7 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"22"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"df748a89-3141-435c-9ac2-831780b8c159","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"古明地, 秀治"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"重見, 開"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"三橋, 匠"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"飯村, 康司"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 皓晴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"菅野, 秀宣"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"篠田, 浩一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田中, 聡久"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shuji, Komeiji","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kai, Shigemi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takumi, Mitsuhashi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yasushi, Iimura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroharu, Suzuki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hidenori, Sugano","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Koichi, Shinoda","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Toshihisa, Tanaka","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10442647","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8663","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"侵襲的 brain–machine interface（BMI）は，人間の脳から直接脳波を取得することで，音声コミュニケーションを実現する技術として期待されている．本稿では，Transformer エンコーダを取り入れた sequence-to-sequence （Seq2seq）モデル（Transformer Seq2seq）により，文発声時の頭蓋内脳波からテキストをデコードする．Transformer は，自然言語処理や音声認識の分野で実績のあるニューラルネットモデルであり，入出力系列間の長期的な依存関係を学習する．てんかん治療のため頭蓋内に電極を留置した 7 名による文発声時における頭蓋内脳波を計測し，Transformer Seq2seq モデルにより発声テキストのデコーディングを試みた． その結果，実験参加者の中で最も高い文節誤り率は 16.4% を達成した．また，このモデルによると全参加者の文節誤り率 の中央値（± 標準偏差）は 31.3（± 10.0%）であった．このことは，頭蓋内脳波からのテキストデコーディングに，Transformer が有効であることを示している．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Invasive brain–machine interfaces (BMIs) are a promising neurotechnology for achieving direct speech communication from a human brain but face many challenges. This paper measured the invasive electrocorticogram (ECoG) signals from seven participating epilepsy patients as they spoke a sentence consisting of multiple phrases. A Transformer encoder was incorporated into a “sequence-to-sequence” model (Transformer Seq2seq) to decode spoken sentences from the ECoG. A Transformer is a successful neural network model for natural language processing and automatic speech recognition. The decoding test revealed that the use of the Transformer model achieved a minimum phrase error rate of 16.4% for one best participant; moreover, the median (± standard deviation) of PER for the Transformer Seq2seq across seven participants was 31.3% (±10.0%). This result showed that the Transformer Seq2seq effectively decoded from ECoG.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告音声言語情報処理（SLP）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-02-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"28","bibliographicVolumeNumber":"2022-SLP-140"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":216629,"updated":"2025-01-19T15:47:20.004219+00:00","links":{},"created":"2025-01-19T01:17:09.150115+00:00"}