The Science Behind AI Speech Recognition with Deepgram's Andrew Seagraves

Deepgram's VP of Research Andrew Seagraves joins to explore the science and engineering behind modern speech recognition systems. Hermes and Andrew dive deep into why speech recognition isn't a solved problem, the two-stage training process of speech-to-text models, and the challenges of balancing real-time latency with accuracy. The conversation covers Deepgram's origins from dark matter research, power laws in speech data, buffer-based architectures for real-time transcription, and frontier challenges like multilingual code-switching, emotion detection, and conversational dynamics. Andrew shares insights on model deployment, customer use cases from NASA to food ordering, and the future of self-adapting speech models.

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