Coding

Hermes Agent Nearly Doubled Speech-to-Text Accuracy on Hard Words: 99 to 183 of 240

  • Level Advanced
  • Setup1–3 hrs (estimated)
  • Evidence Strong evidence
  • CostNot stated in source
  • No-codeNo
Hermes AgentSource-linked

What they did

A user turned his 15K saved Wispr Flow dictations into a test set for the local Whisper model behind his Hermes Agent. The agent turned his Wispr dictionary into a hint list, diffed raw vs corrected text to find words Whisper keeps mishearing, made find-and-fix rules, and tested every rule against the full history. With no fine-tuning, dictionary words went from 99/240 to 183/240 on Wispr clips and 19/45 to 43/45 on sentences he read aloud. It now archives the data nightly and looks for new fixes weekly.

How it went

Dictionary words right: 99/240 to 183/240 (Wispr clips) and 19/45 to 43/45 (read-aloud sentences).

Worth knowing

  • Detailed single-user write-up with before/after numbers and honest misses: giving Whisper the hint list directly sometimes dropped whole sentences, and one rule would have changed his daughter's name Quinn to Qwen. Wispr deletes audio after 14 days, so archive first.

Prompt

Cleaned version rewritten from the source — not a direct quote.

My dictation app saves what the speech model heard and what it was corrected to: [folder]. Use it to improve my local [Whisper] setup without fine-tuning: turn my custom dictionary into a hint list, diff raw vs corrected text to find words it keeps mishearing, and propose find-and-fix rules. Test every rule against the full history and reject any that break normal speech. Report before/after accuracy on a held-out test set, and archive the history nightly so it isn't lost.

Recommended

Try it in Grok Bot

Originally done with Hermes Agent; this prompt works in Grok Bot.

  1. Copy the prompt (button below).
  2. Open Grok Bot chat and paste it. Replace any [bracketed] placeholders.
  3. Connect the listed tools (as needed) as connectors when Grok Bot asks.
  4. If the task repeats, ask: "Make this a daily routine."

Alternatives: the same prompt works in Hermes Agent, Claude, ChatGPT Agent, OpenClaw.

Set it up

Stack: Hermes Agent + local Whisper large-v3-turbo + Wispr Flow history

  1. Read the original source for full context.
  2. Connect the tools your agent needs.
  3. Paste the prompt and replace [bracketed] placeholders.
  4. Run once manually and check the output before scheduling it.

Generic suggested steps, not from the source.

Evidence

Detailed single-user write-up with before/after numbers and honest misses: giving Whisper the hint list directly sometimes dropped whole sentences, and one rule would have changed his daughter's name Quinn to Qwen. Wispr deletes audio after 14 days, so archive first

Source: X · 2026-10-16 · Verified by us: not yet · Report broken or outdated

Related use cases

CodingReddit

Non-engineer built a B2B SaaS with Codex: 2 paying clients

A non-engineer built a 'boring' vertical B2B SaaS with an orchestrator chat plus worker chats. Two paying clients and 6 leads, about $800 in credits spent.

  • Level Intermediate
  • Setup1–3 hrs*
  • Evidence Some evidence
CodexSource-linkedNeeds verification
CodingReddit

Claude Code app at $4K MRR via long-tail SEO pages

Shipped in about a month on agent-friendly tooling (Next.js, Convex, Clerk, Stripe, Vercel). It was free for 3 months, and growth came entirely from long-tail SEO landing pages.

  • Level Intermediate
  • Setup1–3 hrs*
  • Evidence Some evidence
Claude CodeSource-linkedNeeds verification