Feedback: speech-to-text-pre-recorded-audio-key-terms-prompting
Documentation Feedback
Section titled “Documentation Feedback”Original URL: https://assemblyai.com/docs/speech-to-text/pre-recorded-audio/key-terms-prompting
Category: speech-to-text
Generated: 05/08/2025, 4:25:20 pm
Claude Sonnet 4 Feedback
Section titled “Claude Sonnet 4 Feedback”Generated: 05/08/2025, 4:25:19 pm
Technical Documentation Analysis: Key Terms Prompting
Section titled “Technical Documentation Analysis: Key Terms Prompting”Overall Assessment
Section titled “Overall Assessment”This documentation covers a useful feature but has several clarity and completeness issues that could frustrate users. Here’s my detailed feedback:
❌ Critical Issues
Section titled “❌ Critical Issues”1. Confusing Keyword Counting System
Section titled “1. Confusing Keyword Counting System”Problem: The documentation contradicts itself on how keywords are counted.
- States “up to 1000 domain-specific words or phrases”
- Later says “Each word in a multi-word phrase counts towards the 1000 keyword limit”
- Example shows only 3 items but implies complex tokenization
Fix: Provide a clear counting table:
Examples of keyword counting:• "hypertension" = 1 token• "differential diagnosis" = 2 tokens• "Wellbutrin XL 150mg" = 3 tokens• Total in example: 6 tokens used of 1000 limit2. Missing Error Handling
Section titled “2. Missing Error Handling”Problem: No guidance on what happens when limits are exceeded or invalid terms are provided.
Add:
- HTTP error codes and responses for limit exceeded
- Validation rules for acceptable terms
- How the system handles rejected keywords
3. Vague Performance Claims
Section titled “3. Vague Performance Claims”Problem: Claims about “contextual understanding” and “semantic meaning” are unsupported.
Improve: Add a concrete before/after example showing actual transcription improvements.
🔧 Structure & Organization Issues
Section titled “🔧 Structure & Organization Issues”4. Misleading Title Hierarchy
Section titled “4. Misleading Title Hierarchy”The page has two H1 headers which creates confusion. Structure should be:
# Key Terms Prompting## Fine-tuning with keyterms_prompt## How It Works## Implementation Examples## Best Practices## Troubleshooting5. Missing Prerequisites Section
Section titled “5. Missing Prerequisites Section”Add upfront:
- Required API key setup
- Slam-1 model availability/pricing implications
- Audio format requirements
📝 Content Gaps
Section titled “📝 Content Gaps”6. No Best Practices Guidance
Section titled “6. No Best Practices Guidance”Add section:
## Best Practices- Use domain-specific terminology most likely to be misheard- Include common abbreviations and acronyms from your field- Add proper nouns, brand names, and technical terms- Avoid extremely common words that are rarely mistranscribed7. Missing Use Case Examples
Section titled “7. Missing Use Case Examples”Add domain-specific examples:
- Medical: drug names, procedures, anatomical terms
- Legal: case names, legal terminology
- Technical: product names, technical specifications
8. No Troubleshooting Section
Section titled “8. No Troubleshooting Section”Add:
- What to do if transcription quality doesn’t improve
- How to identify which terms are actually being recognized
- Performance impact of using maximum keyword limits
🔍 Code Examples Issues
Section titled “🔍 Code Examples Issues”9. Incomplete Error Handling
Section titled “9. Incomplete Error Handling”The Python example only checks for HTTP 200 but doesn’t handle:
- Network timeouts
- Invalid API keys
- Malformed responses
- Transcription service errors
10. Missing Response Format Documentation
Section titled “10. Missing Response Format Documentation”Show what the actual API response looks like, including:
- Full response schema
- How keywords affect confidence scores
- Any metadata about keyword usage
🎯 User Experience Improvements
Section titled “🎯 User Experience Improvements”11. Add Interactive Elements
Section titled “11. Add Interactive Elements”- Token counter tool to help users estimate their usage
- Template keyword lists for common industries
- Success metrics explanation (how to measure improvement)
12. Missing Integration Context
Section titled “12. Missing Integration Context”Add:
- How this feature works with other AssemblyAI features
- Performance/cost implications
- When NOT to use key terms prompting
📋 Specific Actionable Fixes
Section titled “📋 Specific Actionable Fixes”Immediate Changes:
Section titled “Immediate Changes:”- Fix the counting explanation with a clear formula and examples
- Add error response examples with HTTP codes
- Include a realistic before/after transcription example
- Add input validation rules (special characters, length limits, etc.)
Content Additions:
Section titled “Content Additions:”- Create a “Quick Start” section with a 3-step process
- Add FAQ section addressing common misconceptions
- Include performance benchmarks or expected improvement ranges
- Add troubleshooting flowchart
Code Improvements:
Section titled “Code Improvements:”- Add comprehensive error handling to all code examples
- Include response parsing examples showing how to access results
- Add validation code for keyword format and limits
- Provide async/await alternatives for better JavaScript examples
This documentation would benefit from user testing to identify additional pain points and validation of the technical accuracy of the keyword processing claims.