In this special montage episode of the Convo AI World Podcast, host Hermes Frangoudis brings together leading researchers and founders from across the speech‑to‑text space to unpack the voice pipeline from the ground up. The conversation covers how cascading architectures stack up against real‑time speech‑to‑speech systems, why Voice Activity Detection acts as the critical traffic controller, and how enterprises can eliminate model pathologies like hallucinations and omissions through modular “Lego block” integration. Guests from Deepgram, Agora, Soniox, and Rime share hard‑won lessons on achieving near‑native accuracy across 60 languages with self‑supervised learning, taming unpredictable pronunciations in LLM‑driven agents, and why truly human‑like emotional understanding is still around the corner. The episode confronts the persistent myth that speech recognition is a solved problem, spotlighting the long tail of accents, rare words, and noisy real‑world conditions that still break most systems, and makes the case that for regulated, high‑stakes industries the auditable text backbone of cascading pipelines remains essential even as speech‑to‑speech models race toward a more natural future.

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