Throughout this week, my primary focus was on intensifying my efforts within the realm of the literature review. I engaged in meaningful discussions with PhD students, collaborating closely with them to enhance the clarity and organization of our charted papers for analysis in the literature review. Leveraging the capabilities of Atlas.ti, we systematically reviewed and extracted crucial data from the selected papers.

The meticulous charting process involved capturing details such as author information, publication year, study specifics, and key findings. This methodical approach allowed us to create a comprehensive overview that served as a foundation for addressing our research questions. Specifically, we delved into questions like:

RQ1: Across HCI, ML/NLP, and Linguistics - How are researchers discussing and addressing fairness, bias, and equity in ASR for ethnic and linguistic minority speakers (Black speakers of AAVE)?

Our exploration encompassed background context on issues of fairness and discussions surrounding equity in ASR. We meticulously examined examples and types of fairness-related harms and bias, including racial bias, gender bias, ability bias, and fairness harms. The implications of bias in ASR on minority speakers were carefully considered, paving the way for a nuanced understanding of the challenges at hand.

Moreover, my focused efforts during the week were directed at gathering pertinent papers related to ethnic and linguistic minority American English-speaking groups. This included a specific emphasis on African American English speakers/users and Chicano speakers. By curating a robust collection of literature, our aim is to contribute to a more comprehensive understanding of the nuanced issues surrounding fairness, bias, and equity in ASR for these specific linguistic communities.