{"id":3073,"date":"2019-11-13T14:33:50","date_gmt":"2019-11-13T19:33:50","guid":{"rendered":"https:\/\/portfolios.cs.earlham.edu\/?p=3073"},"modified":"2025-04-15T14:56:18","modified_gmt":"2025-04-15T18:56:18","slug":"cs388-week-11-update-3","status":"publish","type":"post","link":"https:\/\/portfolios.cs.earlham.edu\/index.php\/2019\/11\/13\/cs388-week-11-update-3\/","title":{"rendered":"CS388 &#8211; Week 11 &#8211; Update"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">I discussed my proposal draft with my advisor. I got her feedback and suggestion, and knew how to revise and improve my proposal. In the past week, I read more papers about the GMM-UBM modeling method that I plan to use for my project. I understood the specific procedure now but it is still hard to fully understand this principle&#8230; Now my another problem is to find a suitable dataset and decide if my system is text-dependent. There are three primary ways for speaker verification now:&nbsp;text-dependent, mixed,&nbsp;text-independent. The&nbsp;text-independent way is very difficult and complicated to do because user can say anything to pass the verification. But&nbsp;text-dependent way is restricted and not safe for spoofing attacks. For example, people can replay pre-recorded voice to pass the verification. Therefore, the mixed way is better. It restricts the text in a way but safe for spoofing attacks. For example, they user can only speak numbers one &#8211; ten, but every time the text is random. But it is hard to find a dataset of all audio file in numbers in English. Now I need to decide which text way my system will use.&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>I discussed my proposal draft with my advisor. I got her feedback and suggestion, and knew how to revise and improve my proposal. In the past week, I read more papers about the GMM-UBM modeling method that I plan to use for my project. I understood the specific procedure now but it is still hard &#8230; <a title=\"CS388 &#8211; Week 11 &#8211; Update\" class=\"read-more\" href=\"https:\/\/portfolios.cs.earlham.edu\/index.php\/2019\/11\/13\/cs388-week-11-update-3\/\" aria-label=\"Read more about CS388 &#8211; Week 11 &#8211; Update\">Read more<\/a><\/p>\n","protected":false},"author":54,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[80,19,100],"tags":[],"class_list":["post-3073","post","type-post","status-publish","format-standard","hentry","category-80","category-student","category-yuqian-zhang"],"_links":{"self":[{"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/posts\/3073","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/users\/54"}],"replies":[{"embeddable":true,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/comments?post=3073"}],"version-history":[{"count":1,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/posts\/3073\/revisions"}],"predecessor-version":[{"id":3074,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/posts\/3073\/revisions\/3074"}],"wp:attachment":[{"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/media?parent=3073"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/categories?post=3073"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/tags?post=3073"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}