{"version":"1.0","provider_name":"Microsoft Research","provider_url":"https:\/\/www.microsoft.com\/en-us\/research","author_name":"Michael Levit","author_url":"https:\/\/www.microsoft.com\/en-us\/research\/people\/mlevit\/","title":"Don't Count on ASR to Transcribe for You: Breaking Bias with Two Crowds - Microsoft Research","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"clqfNDTfal\"><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/dont-count-asr-transcribe-breaking-bias-two-crowds\/\">Don&#8217;t Count on ASR to Transcribe for You: Breaking Bias with Two Crowds<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/dont-count-asr-transcribe-breaking-bias-two-crowds\/embed\/#?secret=clqfNDTfal\" width=\"600\" height=\"338\" title=\"&#8220;Don&#8217;t Count on ASR to Transcribe for You: Breaking Bias with Two Crowds&#8221; &#8212; Microsoft Research\" data-secret=\"clqfNDTfal\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/* ]]> *\/\n<\/script>\n","description":"A crowdsourcing approach for collecting high-quality speech transcriptions is presented. The approach addresses typical weakness of traditional semi-supervised transcription strategies that show ASR hypotheses to transcribers to help them cope with unclear or ambiguous audio and speed up transcriptions. We explain how the traditional methods introduce bias into transcriptions that make it difficult to objectively [&hellip;]"}