Fix Transcription Errors

The short answer: enable Recognition Fix at the Polish level to automatically correct most transcription errors during processing.

Accents, technical terms, and background noise often produce "creative" interpretations that make your text look unprofessional. AICHE's AI enhancement pipeline fixes these automatically - but you need to pick the right level for your situation.

The Three Recognition Fix Levels

AICHE offers three levels of post-transcription cleanup. Each adds a small amount of processing time but dramatically improves output quality.

Light

Fixes obvious misrecognitions without changing your wording. Corrects things like "their" vs "there," capitalizes proper nouns, and fixes number formatting. Processing adds less than 1 second. Use Light when you want minimal changes - for example, when dictating a casual message where your natural phrasing matters more than polish.

Medium

Everything in Light, plus grammar smoothing and filler word removal. Strips out "um," "uh," "like," and "you know" while preserving your meaning. Restructures run-on sentences into cleaner phrasing. Adds 1-2 seconds of processing. This is the best default for most people - it cleans up your speech without making it sound robotic.

Polish

Maximum accuracy. Everything in Medium, plus full sentence restructuring, punctuation optimization, and context-aware corrections. Polish understands that "react" in a coding conversation is a framework name, not a verb. Adds 2-3 seconds of processing but catches roughly 95% of errors. Use Polish for anything professional - emails to clients, documentation, reports.

How to Enable Recognition Fix

1. Open AICHE settings before recording.
2. Find Recognition Fix under AI Enhancements.
3. Select your preferred level (Polish recommended for most use cases).
4. Record your content normally with ⌃+⌥+R (Mac) or Ctrl+Alt+R (Windows/Linux).
5. Review the output - most specialized terms will be handled correctly.

The setting persists across recordings, so you only need to set it once.

Common Error Types and How to Handle Them

Homophones

Words that sound alike but have different meanings - "their/there/they're," "to/too/two," "its/it's." Medium and Polish levels handle these using sentence context. If you say "send it to there team," Polish corrects it to "send it to their team."

Technical Jargon

Industry terms, product names, and acronyms are the hardest for any transcription system. Polish level uses context to identify these - if the surrounding words are technical, it adjusts. For consistently misrecognized terms, speak them slightly slower the first time in a recording. The AI picks up context from that initial usage.

Numbers and Formatting

Raw transcription often writes out numbers ("one hundred twenty three") when you want digits ("123"). Medium and Polish levels apply smart number formatting based on context - dates, dollar amounts, percentages, and counts get converted to their expected format.

Proper Nouns

Names of people, companies, and places can be mangled by raw transcription. Polish level cross-references common proper nouns and corrects capitalization. For uncommon names, spelling them out the first time helps: "Send this to Priya - P-R-I-Y-A."

Environment Tips for Better Base Accuracy

Recognition Fix works best when the raw transcription is reasonably close. These tips reduce errors before AI enhancement even kicks in:

• Microphone distance. Keep your mic 6-10 inches from your mouth. Too close picks up plosives (harsh "p" and "b" sounds); too far picks up room echo.
• Background noise. In noisy environments, a directional microphone or headset makes a bigger difference than any software setting.
• Speaking pace. Your natural pace is fine. Speaking too slowly actually introduces more errors because the AI expects natural speech rhythm.
• Hydration. Dry mouth causes slurred consonants. Keep water nearby for long dictation sessions.

Comparing Results

Raw transcription accuracy typically sits around 85-90% for clear speech in a quiet environment. With Polish enhancement enabled, that jumps to 97-98%. On a 500-word dictation, that's the difference between 50-75 errors and 10-15 - most of which are edge cases with uncommon proper nouns.

Do this now: record a technical sentence with Recognition Fix disabled, then record the same sentence with Polish enabled. Compare the two outputs to see the difference firsthand.