It is common for many of us to change the way we speak so that voice-activated systems (such as Siri, Alexa) understand us! This is called bias in speech technology, where the technology works best only for speakers of well-resources languages such as American English. For speakers of other languages/accents such as Ne Zealand English, the technology does not work as well.
As voice-activated systems become increasingly integral to our daily lives, understanding and mitigating bias in these technologies is paramount. This project aims to uncover the hidden biases present in speech technology, utilising a multidimensional approach that encompasses linguistic, cultural, and demographic factors.
Firstly, we will try to define what bias in speech technology is (we all know that the technology is biased, but can we define what bias is!). Secindly, we will propose aproaches to reduce bias in speech technology.
The skills needed for the project are a vision contribute to fair technology development using your engineering education, coding skills (R, Python), basics of machine learning and the willingness to learn. Intrest in linguistics and signals (such as music) is a bonus!
The project will contribute valuable insights to the ongoing discourse on ethical AI and inclusive technology development.
Undergraduate
None
Signal Processin (405.722, Lab)