Voice AI Is Moving Beyond Audio Transcription
In this episode, Carter Huffman, CTO and co-founder of Modulate, joins AI journalist Craig Smith to break down how real-time voice intelligence is unlocking an entirely new layer of AI, one that goes far beyond audio to text transcription.
In this episode, Carter breaks down how modern audio analytics and conversational AI systems can extract intelligence directly from live voice conversations instantly and at scale.
You’ll learn how AI for audio is powering:
● Real-time voice moderation in online games
● Automated speech emotion recognition
● Fraud detection and scam prevention
● Deepfake voice detection
● Sentiment analysis for financial markets
● Enterprise audio analytics and conversational insights
“You don’t just want a transcript of what’s being said — you want to really understand what’s going on.”
— Carter Huffman
Why this episode matters for your team
For years, voice AI meant speech-to-text transcription. Today, it means something much bigger.
Most of the market still equates voice AI with speech-to-text and transcription. This episode explains why that layer is becoming commoditized — and why the real opportunity is in real-time conversational intelligence
Instead of defaulting to ever-larger foundation models, Modulate is pioneering a dynamic ensemble-of-ensembles architecture.
Tens of billions of digital voice conversations happen daily. Almost none are deeply analyzed beyond transcription.
Analyze behavior across millions of hours of concurrent conversations. Learn how an ensemble model AI achieves ultra-low latency under distributed system constraints.
Discover more conversations that decode modern voice AI challenges.
Our team will review submissions and answer the most important ones in the next episode.
Fill out the form to submit your topic, scenario, challenge, or question. Our team will review submissions and feature the most important ones in the next episode.
— The Modulate Team