What happens to language when machines start talking back?

BlackJack3D / Getty Images A few months ago, a friend posted something that caught my eye on social media.

She struggled listening to what she termed “(literally) breathless AI voices for audiobooks”.

When I asked her what part she found the most off-putting, she said she had to stop listening because there was no natural breathing or variation – it’s just too formulaic.

This might seem like a small complaint.

But it points to a much bigger question about language and artificial intelligence: what happens when we design systems to produce language without paying enough attention to the people who listen to it or read it? Communication does not begin and end with the speaker.

Listeners work just as hard: attending not just to what someone says, but how they say it, what has just happened and what we expect might happen next.

Even what we regard as imperfections in speech can carry information.

Disfluencies have meaning Linguists often use the word “disfluencies” to refer to hesitations, repetitions, false starts and other departures from “fluent” speech.

The label can make them sound like defects that ought to be removed.

But in human conversation, they are part of the message .

A synthetic voice that strips out disfluency may be grammatically accurate and acoustically flawless, yet feel impoverished to the listener, who simply has less to work with.

We are not simply decoding signs Language does not exist in our minds merely as a catalogue of words and how they are pronounced and used.

It is entangled with memory, experience and our knowledge of the world, shaped by where we grew up, with whom, doing what and for what purpose.

Award-winning author Arundhati Roy captures something of this in her memoir Mother Mary Comes To Me when she describes most of us as “a living, breathing soup of memory and imagination”.