{"_buckets": {"deposit": "6f1faf14-6975-4d44-87f9-bb5a4fe5cf98"}, "_deposit": {"id": "7871", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "7871"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00007871", "sets": ["314"]}, "author_link": ["22492", "22493", "22494", "22495", "22496", "22497"], "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2006", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "924", "bibliographicPageStart": "v", "bibliographicVolumeNumber": "5", "bibliographic_titles": [{"bibliographic_title": "IEEE International Conference on Acoustics, Speech and Signal Processing", "bibliographic_titleLang": "en"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "Spectral analysis is applied to such driving behavioral signals as gas and brake pedal operation signals for extracting drivers\u0027 characteristics while accelerating or decelerating. Cepstral features of each driver obtained through spectral analysis of driving signals are modeled with a Gaussian mixture model (GMM). A GMM driver model based on cepstral features is evaluated in driver identification experiments using driving signals collected in a driving simulator and in a real vehicle on a city road. Experimental results show that the driver model based on cepstral features achieves a driver identification rate of 89.6 ％ for driving simulator and 76.8 ％ for real vehicle, resulting in 61 ％ and 55 ％ error reduction, respectively, over a conventional driver model that uses raw driving signals without spectral analysis.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/9596"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "IEEE", "subitem_publisher_language": "ja"}]}, "item_10_relation_11": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type": "isVersionOf", "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://doi.org/10.1109/ICASSP.2006.1661427", "subitem_relation_type_select": "DOI"}}]}, "item_10_relation_8": {"attribute_name": "ISBN", "attribute_value_mlt": [{"subitem_relation_type": "isPartOf", "subitem_relation_type_id": {"subitem_relation_type_id_text": "1-4244-0469-X", "subitem_relation_type_select": "ISBN"}}]}, "item_10_rights_12": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "Copyright © 2006 IEEE. Reprinted from (relevant publication info). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Nagoya University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org.", "subitem_rights_language": "en"}]}, "item_10_select_15": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_10_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "1520-6149", "subitem_source_identifier_type": "PISSN"}]}, "item_10_text_14": {"attribute_name": "フォーマット", "attribute_value_mlt": [{"subitem_text_value": "application/pdf"}]}, "item_1615787544753": {"attribute_name": "出版タイプ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_970fb48d4fbd8a85", "subitem_version_type": "VoR"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "open access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_abf2"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Miyajima, C.", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "22492", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Nishiwaki, Y.", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "22493", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Ozawa, K.", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "22494", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Wakita, T.", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "22495", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Itou, K.", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "22496", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Takeda, K.", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "22497", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2018-02-19"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "Miyajima1.pdf", "filesize": [{"value": "200.2 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_note", "mimetype": "application/pdf", "size": 200200.0, "url": {"label": "Miyajima1.pdf", "objectType": "fulltext", "url": "https://nagoya.repo.nii.ac.jp/record/7871/files/Miyajima1.pdf"}, "version_id": "e47980c9-ec83-4315-9243-968c11348c90"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "Cepstral Analysis of Driving Behavioral Signals for Driver Identification", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Cepstral Analysis of Driving Behavioral Signals for Driver Identification", "subitem_title_language": "en"}]}, "item_type_id": "10", "owner": "1", "path": ["314"], "permalink_uri": "http://hdl.handle.net/2237/9596", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2008-03-17"}, "publish_date": "2008-03-17", "publish_status": "0", "recid": "7871", "relation": {}, "relation_version_is_last": true, "title": ["Cepstral Analysis of Driving Behavioral Signals for Driver Identification"], "weko_shared_id": -1}