docs/AI_FEATURES.md

AI & Context Features

The MV Subtitle Generator isn't just a transcriber; it's a context-aware editor. This document explains how the AI works to give you better results.

The Problem with Traditional Transcription

Standard Speech-to-Text engines often struggle with:

• Homophones: Words that sound the same but mean different things (e.g., pair vs pear, date a vs data).
• Specialized Jargon: Technical terms often get transcribed as common words.
• Names: Unique names are often misspelled.

Our Solution: Context Injection

We use a sophisticated LLM (Large Language Model) review stage. When you provide context during upload, we pass this directly to the AI's "brain" when it reviews your text.

How it works

1. Transcription: The audio is converted to raw text.
2. Semantic Analysis: The AI reads the text and your provided context.
3. Cross-Referencing: It asks: "Does this word make sense given the user said this is a medical lecture?"

Examples

Context Provided	Audio Heard	Bad Transcription	MV AI Correction
"Programming tutorial"	"We need to verify the code"	"We need to very fry the code"	"verify"
"Financial report"	"The company's machine earning"	"machine earning"	"machine learning"
"Biology class"	"Look under the mike row scope"	"mike row scope"	"microscope"

Auto-Tidy (Confidence Scoring)

The AI assigns a Confidence Score (0-100%) to every potential error it finds.

• High Confidence (100%) -> Auto-Fix: If the AI is virtually certain it's a mistake (e.g., specific known typo or grammar rule failure), it will automatically fix it before you even see the review screen. These appear as "Auto-applied" in your review list.
• Medium Confidence -> Suggestion: If it's unsure, it flags it as an "Anomaly" and asks for your human review, providing a reason and a suggestion.

Getting the Best Results

To maximize accuracy:

1. Be Specific: Instead of just "Meeting", try "Quarterly marketing meeting discussing Q4 budget and ROI".
2. List Terms: "Keywords: React, TypeScript, API, Database".
3. Name Names: "Speakers: John, Sarah, and Dr. Emily".