When Low Word Error Rate Still Breaks a Voice Product

Word error rate remains useful for measuring transcript quality, but production voice systems care more about critical-value recovery and end-to-end task success.

Voice AI Is a Workflow Problem Now

As voice models get good enough, the bottleneck moves from the model to the operating layer around it: the inputs, the workflow, the human-in-the-loop, and the discipline of rollout.

The Proper Noun Problem in Speech Recognition

A fluent transcript can still fail the words that carry identity and meaning, so ASR evaluation needs entity-level metrics alongside overall word error rate.

The Most Boring Voice AI Deployment Is Answering Your Phone

While the industry's attention is on reasoning models and agentic workflows, the voice AI use case with the clearest, most measurable return today is picking up the phone when a small business can't.

The Voice Can Sound Right, and the Video Can Still Be Wrong

A believable voice is only one part of successful localization; the translation, speakers, timing, captions, and publishing details must also work together in the finished video.

Why Better Client Tracking Starts With Better Capture of Spoken Clinical Interactions

Modern AI-powered speech recognition and audio capture tools improve clinical documentation accuracy, streamline client tracking, reduce provider burnout, and enhance patient care.

From Large Language Models to Conversational Awareness

Why enterprise voice AI must learn to understand human interaction

Why Voice AI’s Next Big Challenge Isn’t Accuracy. It’s Relationship Design.

Modern voice AI can't continue to follow the same patterns that held the speech industry back for decades.

Goodhart’s Law Is Eating Your Voice AI Rollout

Here are some common voice AI metrics and where they fail. (Featured on SmartCustomerService.com.)

Voice AI: The Dos, the Don’ts, and What’s Next [Featured on DestinationCRM]

Bridging Speech and Hearing: How Audiology Advances Are Powering Next-Gen Voice Recognition

Advances in audiology are teaching machines to listen and hear similarly to humans, which can increase the quality of voice recognition and other auditory technology.

Why Voice AI Is the Next Frontier in Customer Conversations

Conversational AI is now mature enough to support real, human-sounding voice interaction. (Featured on SmartCustomerService.com.)

Conversation Analytics: A Necessity for AI-Enabled Customer Service

These solutions are a foundational component for contact centers of the future. (Featured on DestinationCRM.com.)

Scaling Trust, Earning Customer Love: The Reality of AI Voice Agents

What it really takes to build an AI voice agent that customers trust and on which teams can rely.

AI vs. AI: How Smart Voice Authentication Builds Customer Trust in the Deepfake Era

Authentic voices and the systems that protect them are the real measure of smart customer service. (Featured on SmartCustomerService.com.)

5 Places for Speech-Language Pathologists to Find Continuing Education Units

Several companies offer courses online, and knowing which one is right for you isn't a difficult process.

The Healthcare Industry's Strategic Advantage Is Now Voice AI

Voice isn't just the interface between humans and systems anymore; it's the intelligence layer binding them together. 

From Chalkboards to Chatbots: Is AI the Future of Teacher Training?

Can Real-Time AI Make Your Contact Center More Compliant or More Vulnerable?

Live AI tools offer significant compliance advantages—if your oversight can keep up.

Hospitality’s New Frontline Risk: AI Voice Fraud

Hospitality businesses are adapting to the rising threat of voice cloning scams by strengthening fraud detection practices and prioritizing real-time intelligence sharing.