MND Diagnosis Leads UK Councillor to AI Voice Solution | eWEEK

MND Diagnosis Leads UK Councillor to AI Voice Solution

Voice tech

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Written By
eWEEK Staff
eWEEK Staff
Jan 20, 2026
3 minute read
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There can be plenty of negative stories around AI, such as ‘slop’ and job cuts, but here’s a positive example.

A UK councillor who struggles to speak after developing motor neurone disease (MND) is using AI technology to communicate using his own pre-recorded voice.

Nick Varley was diagnosed with the neurodegenerative disorder in November 2024 after beginning to have difficulty speaking. Now, through new AI voice-cloning technology, Varley is able to speak with a digital version of his own voice — allowing him to continue taking part in council meetings and community work as his condition progresses.

“It can be very emotional because your voice is such a big part of you, and no one wants it to sound like Stephen Hawking did,” he said.

Californian connection

According to the BBC report, shortly after his diagnosis, Varley began recording his speech, creating an audio archive that could be used to preserve how he sounds. Those recordings were then used to train an AI system to generate a realistic voice model, effectively producing a “synthetic” voice that mirrors his own tone and delivery.

The technology was developed through a partnership between the MND Association and a California-based tech firm called 11Labs, reflecting a wider trend of charities and private companies working together to deliver practical support for people with life-limiting illnesses.

Varley used the tool for the first time in a public setting by asking a question at Sevenoaks District Council’s cabinet meeting in January. For supporters, it marked a symbolic step: proof that people facing progressive loss of speech can still be present and heard in civic spaces.

“It’s amazing because when you get your diagnosis, part of you thinks, ‘my life is over’,” he said.

“And being able to still work, still talk, and still participate is amazing.”

Why voice matters in MND

MND affects nerves found in the brain and spinal cord, which tell your muscles what to do. As those nerves become damaged, muscles weaken and stiffen over time. The condition can affect mobility and independence, but it also commonly impacts some of the most basic functions of daily life — including how people walk, talk, eat, and breathe.

For many people living with MND, the loss of speech is one of the most distressing changes because it alters how they communicate with friends, family, and colleagues. In public roles such as politics, the ability to speak clearly can be central to the job, whether in debates, community meetings, media interviews, or representing residents’ concerns.

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A shift in assistive technology

While communication aids for MND are not new, AI voice technology marks an important shift. Traditional text-to-speech devices often rely on generic computer-generated voices that may sound robotic or unfamiliar, sometimes making people feel disconnected from their identity. They can also carry unintended social stigma, particularly in settings where confidence and public perception matter.

By contrast, voice cloning allows someone’s own manner of speaking to be preserved. That has both personal and professional implications. Being able to “sound like yourself” may help people maintain relationships, confidence, and independence, while also allowing them to remain active in the workplace or in public roles.

Looking ahead

For Varley, the ability to keep speaking in his own voice is not just a technical achievement — it is a way of continuing his life and public service while living with a degenerative condition.

His experience illustrates both the challenges of MND and the potential of new technologies to protect communication, identity, and participation.

As AI tools become more accessible, they may increasingly be seen not as luxury innovations, but as essential support for people whose voices are at risk of being lost.

Kyutai has released Pocket TTS, a text-to-speech model so small (100 million parameters) it runs faster than real-time on your CPU.

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