Most teams that want an in-house ASR, TTS, or speech translation service face the same messy choice: glue together fragments of ESPnet, NeMo, k2, and HuggingFace, or hand everything to a cloud API and pay per minute forever. Tycho is a toolkit built to short-circuit that decision — a single stack for fine-tuning and customizing state-of-the-art pretrained speech models, then evaluating and deploying them with an eye on ROI rather than benchmark bragging rights.

This overview lays out what Tycho covers end-to-end: fine-tuning SOTA foundation models on curated datasets, customizing them with new features and adapters, running honest evaluations, and deploying them in a way that survives production traffic. It also touches on the research-oriented path — training your own large speech model from scratch with reference recipes and paper summaries as scaffolding. If you're weighing build-versus-buy for a voice product, or you're tired of stitching four half-maintained repos together to ship one ASR endpoint, the walkthrough is a useful map of what a modern in-house speech stack can actually look like.