<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data Annotation | Lee-Ann Vidal Covas, PhD</title><link>https://leeannvc.com/tags/data-annotation/</link><atom:link href="https://leeannvc.com/tags/data-annotation/index.xml" rel="self" type="application/rss+xml"/><description>Data Annotation</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><image><url>https://leeannvc.com/media/logo_hu_408c0977b7e48a52.png</url><title>Data Annotation</title><link>https://leeannvc.com/tags/data-annotation/</link></image><item><title>Cogito: Speech Data Annotation for Machine Learning</title><link>https://leeannvc.com/tech_projects/cogito/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://leeannvc.com/tech_projects/cogito/</guid><description>&lt;h2 id="overview"&gt;Overview&lt;/h2&gt;
&lt;p&gt;Worked on annotation and quality assurance for speech and language datasets used in machine learning models, focusing on improving model performance and annotation consistency.&lt;/p&gt;
&lt;h2 id="my-role"&gt;My Role&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Annotated speech data for emotion, engagement, and speech patterns&lt;/li&gt;
&lt;li&gt;Designed and refined annotation approaches across projects&lt;/li&gt;
&lt;li&gt;Conducted prompt engineering to improve model outputs&lt;/li&gt;
&lt;li&gt;Tested pre-trained language models and suggested calibration improvements&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="data--workflows"&gt;Data &amp;amp; Workflows&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Processed audio and text data for ML training pipelines&lt;/li&gt;
&lt;li&gt;Built and validated annotated datasets for internal and external clients&lt;/li&gt;
&lt;li&gt;Handled dynamic annotation requests across teams&lt;/li&gt;
&lt;li&gt;Contributed to workflow improvements and QA processes&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="impact"&gt;Impact&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Improved annotation consistency across datasets&lt;/li&gt;
&lt;li&gt;Contributed to higher-quality training data for ML models&lt;/li&gt;
&lt;li&gt;Provided insights that informed model behavior and UX decisions&lt;/li&gt;
&lt;/ul&gt;</description></item></channel></rss>