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<div class="" style="word-wrap:break-word"><span class="" style="font-size:14.666666984558105px">This is an announcement of Jenna Cryan's Candidacy Exam.</span><br class="" style="font-size:14.666666984558105px">
<span class="" style="font-size:14.666666984558105px">===============================================</span><br class="" style="font-size:14.666666984558105px">
<span class="" style="font-size:14.666666984558105px">Candidate: Jenna Cryan</span><br class="" style="font-size:14.666666984558105px">
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<span class="" style="font-size:14.666666984558105px">Date: Friday, July 1, 2022</span><br class="" style="font-size:14.666666984558105px">
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<span class="" style="font-size:14.666666984558105px">Time: 11 am CST</span><br class="" style="font-size:14.666666984558105px">
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<span class="" style="font-size:14.666666984558105px">Remote Location: </span><a href="https://urldefense.com/v3/__https://uchicago.zoom.us/j/92491028233?pwd=Q1RwUXM0T1d5SnBLeXhpTkdudkg2UT09__;!!BpyFHLRN4TMTrA!9OnHAtNviGmhNyjNqJz62etdXlKBMdJP9JhPQlGrXc64JT88PYQB8KeK2ELvwLD5otiKYWc8A8EWOhW6-dPjP_wdHEMNhW6C$" class="">https://uchicago.zoom.us/j/92491028233?pwd=Q1RwUXM0T1d5SnBLeXhpTkdudkg2UT09</a> (meeting
ID: 924 9102 8233, password: <span class="" style="color:rgb(35,35,51); font-family:Lato,Helvetica,Arial; font-size:13px">345294)</span><br class="" style="font-size:14.666666984558105px">
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<span class="" style="font-size:14.666666984558105px">Location: JCL 346</span><br class="" style="font-size:14.666666984558105px">
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<span class="" style="font-size:14.666666984558105px">Title: Measuring Perceptions and Mitigating Bias in Text and Voice</span><br class="" style="font-size:14.666666984558105px">
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<span class="" style="font-size:14.666666984558105px">Abstract: </span><span class="" style="white-space:pre-wrap; font-size:15px">Our ability as humans to effectively communicate depends heavily on the language we use and the way we speak to one another. The
values of our society are both reflected in and reinforced by our use of language. Detecting how this language could convey bias needs to remain effective as these values evolve over time. Specifically, gendered language in text often affirms gender stereotypes
and often perpetuate bias and discrimination. As we as readers absorb written content, gendered language used settings such as biographies, recommendation letters, and job advertisements can negatively impact the subjects and audiences alike. Gender stereotypes
have been studied extensively, however, the current methods used today still rely on word banks from nearly 50 years ago. Since then, societal views have continued to evolve and it’s important to be able to reflect these changes. Additionally, significant
ad- vances have been made in developing new methods for analyzing how words are used in text. To address this, the methodology of this work proposes updating existing gender lexicons to reflect modern language use, and applying machine learning to detect gendered
language more efficiently. In addition to written text, efficient and unbiased communication depends upon not only the content, but the manner in which it is presented. The tone of voice of a speaker can heavily influence how they are perceived. Particularly,
changes in emotional tone of voice can reduce these inherent biases in the listener, thereby providing more effective communication. This work explores ways to improve methods for measuring perceptions of gendered language in text and emotion tone in voice,
and ways to mitigate resulting biases.</span><br class="" style="font-size:14.666666984558105px">
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<span class="" style="font-size:14.666666984558105px">Advisors: Ben Zhao </span><br class="" style="font-size:14.666666984558105px">
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<span class="" style="font-size:14.666666984558105px">Committee Members: Ben Zhao, Heather Zheng, Marshini Chetty</span>
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