CNN-based audio segmentation toolkit. Allows to detect speech, music, noise and speaker gender. Has been designed for large scale gender equality studies based on speech time per gender.
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Updated
Dec 16, 2024 - Python
CNN-based audio segmentation toolkit. Allows to detect speech, music, noise and speaker gender. Has been designed for large scale gender equality studies based on speech time per gender.
Reading for gender bias
Plain Face Detector & Gender Recognizer
This is an Android App for Women or any Female, which Will Call to an Emergency number, based on a specific voice command like "Help" . It will also send SMS with current GPS coordinates to those numbers.
Menstruated is a place where women share their first-period stories, feelings, emotions through blogs. Can track your periods and get notified early through the mail. They should know that you are not alone in the fight against PCOS by-polls which shown in the graph and many other questions. Can know the myths/facts, self-care during periods.
A Plain Demonstration of Gender Recognition Using DNN
Sakhi, a mobile-first app tailored for women, encompasses daily journals, safety features, community, and holistic health tools. Elevate your well-being with Sakhi, your dedicated companion for empowerment, connection, and growth.
Collection of code in different languages, to check if a name is a danish girl name
this is a calculator that calculate how fat you are
In this App, you can find the details related to females' puberty, periods/menstruation, health issues, and more. The female will get enough information about their body so that they will not be dependent on others.
Transform Your Body and Mind in 30 Days
CSS Chick is an online all-female CSS and HTML boot camp that helps empower women from all over the world!
This Box addresses the Gender Bias of a seemingly objective expert discussion in science. It stresses the problem of underrepresentation of female scientists and their work and displays this visually by the image of an All-Male-Panel. This panel is labeld "Greatest Scientists" and shows Galileo Galilei, Stephen Hawking, Albert Einstein and Erwin…
The model is trained using various layers and the trained model is used for classifying the picture as either male or female.
This is my third assignment in the GA TECH Bootcamp.
Add a description, image, and links to the female topic page so that developers can more easily learn about it.
To associate your repository with the female topic, visit your repo's landing page and select "manage topics."