How to Build a Voicebot That Truly Understands Your Customers
In recent years, more and more companies have started automating administrative tasks.
But in many cases, this automation stops at a chatbot or a self-service portal. The telephone channel, however, remains one of the most challenging to automate, and at the same time, it’s the most valuable. A single phone call is still the most direct, personal, and costly form of customer contact.
In a recent article published on Frankwatching, AssistYou explains what happens “under the hood” when a customer gives their address over the phone and how Voice AI can automate this process while keeping the interaction human and natural.
What happens behind every conversation
When a customer calls their insurance company to report a new address, it sounds like a simple exchange. But to make that process fully automated, four key technologies must work seamlessly together:
Voice Activity Detection (VAD)
Automatic Speech Recognition (ASR)
Language Models (LLMs)
Text-to-Speech (TTS)
These technologies listen, interpret, and respond in real time. Each one plays a critical role in ensuring that a digital voice assistant can understand what the customer says and respond naturally.
Why the phone channel is so complex
Most phone systems still use audio with a sample rate of 8,000 Hz, a far lower quality than the 48,000 Hz we experience with streaming or TV audio. This means that subtle sounds like “six” versus “seven” or “A” versus “H” can easily be misheard. For a human agent, that’s no problem. For a voicebot, it can be the difference between a smooth experience and customer frustration.
How to make Voice AI work
The article highlights several best practices to improve speech recognition in automated phone systems.
These include providing contextual hints (“expect a postcode”), using multiple ASR engines in parallel, applying logical corrections to transcripts, and introducing confidence thresholds to confirm uncertain responses.
By combining these strategies, organizations can dramatically increase the accuracy of their voice assistants and make automated phone conversations feel more reliable and human.
The future of Voice AI
New end-to-end audio models, such as Google Gemini Live are now emerging, combining recognition, understanding, and response in a single system. These models are faster and sound more natural, but they also bring new challenges in terms of control, data safety, and compliance with the upcoming EU AI Act.
Building a truly effective voicebot is not about choosing one smart model. It’s about orchestrating multiple technologies, from speech detection to interpretation in real time, and designing every detail to serve the customer’s experience.
Want to learn how to build a Voice AI assistant that actually understands your customers?
Read the full article from AssistYou on Frankwatching:
👉 How to Build a Voicebot That Truly Understands Your Customers
