This week I assisted in collecting speech data from hearing-impaired children as part of a project to train AI models that can better recognise diverse speech patterns. My role involved supporting the recording sessions—helping set up the environment, prompting the children, and making sure the process was smooth and comfortable for them.

Although the task was technical in nature, what stood out most to me was observing the practical difficulties the children encountered when communicating. Some words took repeated effort to pronounce clearly, while others were substituted or adapted in ways that reflected their individual speech patterns. I also noticed how often children relied on context, expression, or small cues to support what they were saying.

This week gave me a more concrete understanding of the challenges hearing-impaired children face in everyday communication. Rather than seeing these difficulties as abstract “barriers,” I saw firsthand the persistence required to be understood and the strategies children develop to get their message across.

It also made me think about the value of designing technology that adapts to users, rather than expecting users to adapt to technology. Contributing to this kind of data collection showed me how leadership in such projects isn’t only about pushing forward research, but also about staying attentive to the people behind the work—their needs, their frustrations, and their resilience.