Repository containing the open source code of works published at the FBK MT unit.
-
Updated
Jun 17, 2024 - Python
Repository containing the open source code of works published at the FBK MT unit.
Interpseech 2024 - News Topic classification (dataset, evaluation and models source)
Voice activity detection and speaker gender segmentation audiovisual corpus
Code and data for the paper "An Information-Theoretic Approach and Dataset for Probing Gender Stereotypes in Multilingual Masked Language Models" (Findings of NAACL 2022)
NamSor API v2 Java SDK - classify personal names accurately by gender, country of origin, or ethnicity.
Scrape news articles and analyze them using NLP to quantify the gender gap in Canadian mainstream media
Measure and mitigate gender bias in Danish toxicity classifiers and sentiment analysis models.
Website for the paper: Auditing Gender Presentation Differences in Text-to-Image Models
Diving into the challenges of data quality in women's healthcare, exploring real-life stories that highlight the critical need for accurate data collection and its impact on diagnoses, treatment, and pharmaceutical advancements. Shedding light on the persistent issues of gender bias in healthcare and advocating for the importance of quality data.
Materials, de-identified data, and analyses for Gardner & Brown-Schmidt "Biased inferences about gender from names" (2024)
Topic Modeling for Gender Bias on Regional News Corpus
A website that visualises how text embeddings trained on Google News are biased towards gender. It also functions as an open source database to generate text embeddings .
Are brands gendered?: Leveraging Gender bias for Appeal and Engagement
Push back against bias in machine translation
EMNLP 2022: "MABEL: Attenuating Gender Bias using Textual Entailment Data" https://arxiv.org/abs/2210.14975
The project can be split into different sub-projects (easy difficulty: replication of the published meta-analysis for evidence of gender bias in hiring decisions; medium for newer modelling). Requires skills in R and will require some learning on Bayesian modelling.
Using GSS data, this paper tracks public perceptions of women in politics over time, in correlation with demographic factors, political views, and party identification
A corpus of bias-causing ambiguities in translation
GENIA: Study of gender biases in machine learning models using explainable artificial intelligence
👩🎓 Dataset of the paper published in EPJ Data Science
Add a description, image, and links to the gender-bias topic page so that developers can more easily learn about it.
To associate your repository with the gender-bias topic, visit your repo's landing page and select "manage topics."