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| # 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". | |