Podcast on Inclusive Research and Innovation in Science, Technology, Engineering and Mathematics Dr. Claudia Werker

We are halfway through our first season and thought it was time to introduce the host of the podcast series Inclusive Research and Innovation (IRI) in Science, Technology, Engineering and Mathematics (STEM)! In this special mini-episode, research assistant Tian Qing Yen interviews the host of the series Dr. Claudia Werker from Delft University of Technology. Claudia explains how she became interested in IRI in STEM and shares some of the challenges and opportunities she has faced in both doing research on and promoting IRI in STEM.

Speech recognition and processing tools are everywhere – from speech-to-text transcription, to voice commands on your phone, to filtering background noise in video calls. However, many automatic speech recognition systems do not perform as well with diverse speakers, i.e. people with an accent, with a speech impediment, or even young or old speakers. Adjusting this technology to recognize different ways of speaking has the potential to make these systems and the tools that depend on them more accessible and inclusive. What challenges and opportunities are there for developing and using more inclusive speech recognition and processing?

In this episode of our podcast series Inclusive Research and Innovation (IRI) in Science, Technology, Engineering and Mathematics, Dr. Claudia Werker from Delft University of Technology talks to her colleague Dr. Odette Scharenborg from the same university. Dr. Scharenborg’s research looks at how to improve speech recognition systems for non-standard speakers. She explains that while acquiring and processing the varied data she needs for her work is challenging, it has also led to opportunities to connect with diverse speakers, to advocate for them, and to help them practically navigate using speech recognition tools.



Learn more about Dr. Scharenborg's research:

Feng, S., Halpern, B., Kudina, O., & Scharenborg, O. Towards inclusive automatic speech recognition (2024)
Feng, S., Kudina, O., Halpern, B., & Scharenborg, O. Quantifying bias in automatic speech recognition (2021)

It is easy to recognize that social media feeds or search results vary for different people. However, it is less clear how much of that bias comes from the way people interact online, and how much is the result of algorithms that are used to filter or rank content. Scholars trying to disentangle this bias recognize the importance of considering diversity in their research. However, analysing algorithmic biases and ways to avoid or overcome them still comes with many challenges. For instance, how do you involve the perspectives of people who are not represented in datasets? Or how do you define what makes an algorithm “fair”, let alone measure fairness?

In this episode of our podcast series Inclusive Research and Innovation (IRI) in Science, Technology, Engineering and Mathematics (STEM), Dr. Claudia Werker (Delft University of Technology) interviews Prof. Dr. Claudia Wagner from RWTH Aachen University. She shares her vision for an infrastructure platform that could facilitate more inclusive methods and data collection in her field of research.

We have known for decades that human beings have differing symptoms and reactions to treatment in the medical sector. Yet progress regarding inclusive medical research and health seems to be slow. To give an example: trials for developing medical drugs usually only include healthy men between 18 and 45 years of age. This means that these trials do not show how medical drugs work for women, children, elderly people, people with a non-white background and patients with comorbidities. How would medical research and health care have to change be inclusive?

In this episode of our podcast series Inclusive Research and Innovation (IRI) in Science, Technology, Engineering and Mathematics (STEM), Dr. Claudia Werker from Delft University of Technology interviews Dr. Irene Grossmann from the same university. Dr. Grossmann is both a medical surgeon and an expert in how to make health care safe for all patients. She shares with us that collecting and interpreting the right data is crucial for including all patients in medical research and health care. This requires changes in both how we do research and also how we teach our students.

Crash-test dummies have not been mirroring the bodies of women and men of all sizes and shapes. We know from research that women – although less frequently involved in accidents – are more severely injured and more often die if they are. Would diversifying crash-test dummies help make more people more safe and secure? Are there other aspects that will ensure better safety and security protection in automobiles for all human beings?

 

In the first episode of our podcast series Inclusive Research and Innovation (IRI) in Science, Technology, Engineering and Mathematics (STEM), Dr. Claudia Werker from Delft University of Technology interviews three experts from Graz University of Technology about these questions. Dr. Cornelia Lex, Dr. Mario Hirz and Dr. Corina Klug share insights about safety and security in cars. For instance, safety depends on both characteristics of the drivers and passengers such as age and gender, and on other aspects like behaviour. Safety and security in cars also start much earlier than preventing injuries in accidents, particularly with ergonomics and the interior design of cars. Moreover, autonomous cars provide these researchers with additional challenges regarding safety and security.

 

Learn more about consumer safety information for cars mentioned by Dr. Corina Klug (30:22) - https://www.euroncap.com/en