{"id":220,"date":"2023-04-08T16:01:54","date_gmt":"2023-04-08T20:01:54","guid":{"rendered":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/?p=220"},"modified":"2023-04-08T16:07:54","modified_gmt":"2023-04-08T20:07:54","slug":"lisa-xiongs-status-report-for-4-8-2023","status":"publish","type":"post","link":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/2023\/04\/08\/lisa-xiongs-status-report-for-4-8-2023\/","title":{"rendered":"Lisa Xiong\u2019s Status Report For 4\/8\/2023"},"content":{"rendered":"<h5><b>Personal Accomplishments<\/b><\/h5>\n<p><span style=\"font-weight: 400\">There are two changes I added to the NLP algorithm this week. The first one is when deleting all of a certain item, for example, when the customer says \u201cno hamburgers\u201d, instead of using the hard-coded 1000 (a quantity large enough than reasonable numbers), I now use Nina\u2019s getItemQuantity function to retrieve the menu item\u2019s actual quantity and delete that exact number from the order. The second one is automatically changing the word \u201chamburg\u201d to \u201chamburger\u201d when parsing, since the speech recognition system often mishears \u201chamburger\u201d as \u201chamburg\u201d, and the word \u201chamburg\u201d does not commonly appear in fast food orders.<\/span><\/p>\n<p><span style=\"font-weight: 400\">I also have started designing the staff UI. My plan is to make each order appear in a small box, and make the entire page resemble a Kanban board.<\/span><\/p>\n<h5><b>Testing Algorithms<\/b><\/h5>\n<p><span style=\"font-weight: 400\">I have run tests with basic sentence structures for all the menu items, giving the NLP system user input as text and asking it to print out the final order. Two examples of basic sentences will be \u201cI want [quantity] [menu item]\u201d and \u201cCan I get [quantity] [menu item]?\u201d. Some tests with sentences including the removal of menu items also have been conducted, such as \u201cCan I get rid of a [menu item]?\u201d or \u201cNo [menu item]\u201d. My initial plan was to use a timer to test the speed of NLP processing, but I soon realized that the processing speed is far below 1 second so the speed test was no longer necessary. There are no design or use case requirements specifically set for my NLP system or staff UI; the order accuracy metric involving the customer UI, speech recognition, NLP and database will be tested in a later stage with us and volunteers imitating the actual ordering situation.<\/span><\/p>\n<h5><b>Schedule<\/b><\/h5>\n<p><span style=\"font-weight: 400\">I am on track with our old (and updated) schedule (see team status report section for details). I have started working on the staff UI, and I will keep optimizing the NLP system when we test during integration.<\/span><\/p>\n<h5><b>Plans for Next Week<\/b><\/h5>\n<p><span style=\"font-weight: 400\">I will work on the staff UI design next week and aim to get it done before when the next status report is due. If more edge cases of ordering commands arise during the testing process, I will also update the NLP system to accommodate them.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Personal Accomplishments There are two changes I added to the NLP algorithm this week. The first one is when deleting all of a certain item, for example, when the customer says \u201cno hamburgers\u201d, instead of using the hard-coded 1000 (a quantity large enough than reasonable numbers), I now use Nina\u2019s getItemQuantity function to retrieve the &hellip; <a href=\"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/2023\/04\/08\/lisa-xiongs-status-report-for-4-8-2023\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Lisa Xiong\u2019s Status Report For 4\/8\/2023&#8221;<\/span><\/a><\/p>\n","protected":false},"author":688,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[8],"tags":[],"_links":{"self":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/posts\/220"}],"collection":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/users\/688"}],"replies":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/comments?post=220"}],"version-history":[{"count":2,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/posts\/220\/revisions"}],"predecessor-version":[{"id":222,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/posts\/220\/revisions\/222"}],"wp:attachment":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/media?parent=220"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/categories?post=220"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s23-teamd3\/wp-json\/wp\/v2\/tags?post=220"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}