{"updated":"2025-01-20T00:02:23.669380+00:00","links":{},"id":192701,"created":"2025-01-19T00:58:23.735518+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00192701","sets":["1164:5159:9402:9617"]},"path":["9617"],"owner":"44499","recid":"192701","title":["Using Functional Load for Optimizing DPGMM based Zero Resource Sub-word Unit Discovery"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-12-03"},"_buckets":{"deposit":"5ee162b4-ceb4-4d27-bc1e-0eb8e5ffedeb"},"_deposit":{"id":"192701","pid":{"type":"depid","value":"192701","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Using Functional Load for Optimizing DPGMM based Zero Resource Sub-word Unit Discovery","author_link":["450426","450421","450427","450422","450428","450423","450424","450425"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Using Functional Load for Optimizing DPGMM based Zero Resource Sub-word Unit Discovery"},{"subitem_title":"Using Functional Load for Optimizing DPGMM based Zero Resource Sub-word Unit Discovery","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"セッション2 単語獲得・感情認識","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2018-12-03","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Nara Institute of Science and Technology"},{"subitem_text_value":"Nara Institute of Science and Technology／RIKEN, Center for Advanced Intelligence Project AIP"},{"subitem_text_value":"Beijing Language and Culture University"},{"subitem_text_value":"Nara Institute of Science and Technology／RIKEN, Center for Advanced Intelligence Project AIP"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology / RIKEN, Center for Advanced Intelligence Project AIP","subitem_text_language":"en"},{"subitem_text_value":"Beijing Language and Culture University","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology / RIKEN, Center for Advanced Intelligence Project AIP","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/192701/files/IPSJ-SLP18125004.pdf","label":"IPSJ-SLP18125004.pdf"},"date":[{"dateType":"Available","dateValue":"2020-12-03"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLP18125004.pdf","filesize":[{"value":"842.7 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"22"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"d1e516e0-1f1a-42ed-b6d3-543156963a7c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Bin, Wu"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Sakriani, Sakti"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jinsong, Zhang"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Satoshi, Nakamura"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Bin, Wu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Sakriani, Sakti","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jinsong, Zhang","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Satoshi, Nakamura","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":"Unsupervised sub-word discovery of the zero resource language gains attention recently. One of the methods to tackle the problem is using an unsupervised clustering algorithm to recover the discrete phone-like units from the speech, such as the Dirichlet Process Gaussian Mixture Model (DPGMM), which currently achieves top results in the Zero Resource Speech Challenge. However, the DPGMM model is too sensitive to the acoustic variation and often produces too many types of sub-word units. This paper proposes to apply functional load to reduce the size of sub-word units from DPGMM. The functional load is the measurement of how much information in communication is conveyed by contrasts of these units. Then, the aim is to ignore the contrasts of the sub-word units that contribute little in conveying the information of the speech leading to decrease of the number of sub-word classes. We experiment on the official Zerospeech 2015 measuring with ABX error rate.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Unsupervised sub-word discovery of the zero resource language gains attention recently. One of the methods to tackle the problem is using an unsupervised clustering algorithm to recover the discrete phone-like units from the speech, such as the Dirichlet Process Gaussian Mixture Model (DPGMM), which currently achieves top results in the Zero Resource Speech Challenge. However, the DPGMM model is too sensitive to the acoustic variation and often produces too many types of sub-word units. This paper proposes to apply functional load to reduce the size of sub-word units from DPGMM. The functional load is the measurement of how much information in communication is conveyed by contrasts of these units. Then, the aim is to ignore the contrasts of the sub-word units that contribute little in conveying the information of the speech leading to decrease of the number of sub-word classes. We experiment on the official Zerospeech 2015 measuring with ABX error rate.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"2","bibliographic_titles":[{"bibliographic_title":"研究報告音声言語情報処理（SLP）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2018-12-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicVolumeNumber":"2018-SLP-125"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}