Tackling Homophones – ‘This Week in AI’

At ICS.AI, we’re constantly refining our AI solutions to make life easier for our customers and their users. This week, our technical delivery team rolled out a subtle but powerful homophone correction update to our GenAI-powered customer service phone system.

Giving Speech-to-Text an Ear for Accents & Meanings

When people call customer service lines, our AI listens carefully. Thanks to recent advances in recognising accents and dialects, our systems are becoming ever more accessible and inclusive.

Even so, certain words that sound alike but mean very different things — known as homophones — have been known to trip up speech-to-text engines. For example, “deaf” and “death” may be pronounced almost identically, and the speech-to-text system must decide which meaning was intended. Our latest improvements take strides to bridge that gap, ensuring a smoother, more accurate, and more natural experience for every caller.

Balancing understanding with safety

Our systems include important content safety protocols that protect against inappropriate language or misuse, they help ensure conversations remain respectful and safe for all users. These safeguards are an essential feature to ensure appropriate interactions, especially when serving vulnerable residents.

Occasionally, these protocols may temporarily flag benign requests for review, but this represents a tiny fraction of interactions and is continuously refined through our learning process.

Homophones

Homophones, where certain words sound alike but mean different things, are one of the most common issues we’ve seen — for example, a caller may be heard to say, “they have been death since berth” which makes more sense when alternative homophones are applied “they have been deaf since birth”.

Our new correction system automatically catches and fixes these in real time. We’ve trained it to recognise dozens of common English homophones, such as:

• “deaf” / “death”

• "birth" / "berth"

• “flower” / “flour”

• “pair” / “pear”

• “peace” / “piece”

Within just a few days, we were able to move from testing to live production — a reflection of our agile approach, powered by SMART Mesh and a culture of continuous learning.

Why This Matters

This week’s work shows the value of continuous improvement – making the AI smarter and more natural for real human conversations, even when accents and homophones are in play.

That means adapting to different accents and dialects, catching subtle transcription errors, and ensuring that our services are accessible and inclusive for all communities. By designing with diversity in mind, we help councils and organisations provide customer experiences that truly work for every resident.

We make sure our AI systems don’t just work — they work well for everyone.

---