9b724f33e3
## New Skill: video-comparer v1.0.0 - Compare original and compressed videos with interactive HTML reports - Calculate quality metrics (PSNR, SSIM) for compression analysis - Generate frame-by-frame visual comparisons (slider, side-by-side, grid) - Extract video metadata (codec, resolution, bitrate, duration) - Multi-platform FFmpeg support with security features ## transcript-fixer Enhancements - Add async AI processor for parallel processing - Add connection pool management for database operations - Add concurrency manager and rate limiter - Add audit log retention and database migrations - Add health check and metrics monitoring - Add comprehensive test suite (8 new test files) - Enhance security with domain and path validators ## Marketplace Updates - Update marketplace version from 1.8.0 to 1.9.0 - Update skills count from 15 to 16 - Update documentation (README.md, CLAUDE.md, CHANGELOG.md) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
117 lines
4.5 KiB
Markdown
117 lines
4.5 KiB
Markdown
---
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name: transcript-fixer
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description: Corrects speech-to-text transcription errors in meeting notes, lectures, and interviews using dictionary rules and AI. Learns patterns to build personalized correction databases. Use when working with transcripts containing ASR/STT errors, homophones, or Chinese/English mixed content requiring cleanup.
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---
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# Transcript Fixer
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Correct speech-to-text transcription errors through dictionary-based rules, AI-powered corrections, and automatic pattern detection. Build a personalized knowledge base that learns from each correction.
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## When to Use This Skill
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- Correcting ASR/STT errors in meeting notes, lectures, or interviews
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- Building domain-specific correction dictionaries
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- Fixing Chinese/English homophone errors or technical terminology
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- Collaborating on shared correction knowledge bases
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## Quick Start
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**Recommended: Use Enhanced Wrapper** (auto-detects API key, opens HTML diff):
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```bash
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# First time: Initialize database
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uv run scripts/fix_transcription.py --init
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# Process transcript with enhanced UX
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uv run scripts/fix_transcript_enhanced.py input.md --output ./corrected
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```
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The enhanced wrapper automatically:
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- Detects GLM API key from shell configs (checks lines near `ANTHROPIC_BASE_URL`)
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- Moves output files to specified directory
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- Opens HTML visual diff in browser for immediate feedback
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**Alternative: Use Core Script Directly**:
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```bash
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# 1. Set API key (if not auto-detected)
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export GLM_API_KEY="<api-key>" # From https://open.bigmodel.cn/
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# 2. Add common corrections (5-10 terms)
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uv run scripts/fix_transcription.py --add "错误词" "正确词" --domain general
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# 3. Run full correction pipeline
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uv run scripts/fix_transcription.py --input meeting.md --stage 3
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# 4. Review learned patterns after 3-5 runs
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uv run scripts/fix_transcription.py --review-learned
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```
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**Output files**:
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- `*_stage1.md` - Dictionary corrections applied
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- `*_stage2.md` - AI corrections applied (final version)
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- `*_对比.html` - Visual diff (open in browser for best experience)
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## Example Session
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**Input transcript** (`meeting.md`):
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```
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今天我们讨论了巨升智能的最新进展。
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股价系统需要优化，目前性能不够好。
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```
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**After Stage 1** (`meeting_stage1.md`):
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```
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今天我们讨论了具身智能的最新进展。 ← "巨升"→"具身" corrected
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股价系统需要优化,目前性能不够好。 ← Unchanged (not in dictionary)
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```
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**After Stage 2** (`meeting_stage2.md`):
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```
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今天我们讨论了具身智能的最新进展。
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框架系统需要优化，目前性能不够好。 ← "股价"→"框架" corrected by AI
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```
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**Learned pattern detected:**
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```
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✓ Detected: "股价" → "框架" (confidence: 85%, count: 1)
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Run --review-learned after 2 more occurrences to approve
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```
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## Core Workflow
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Three-stage pipeline stores corrections in `~/.transcript-fixer/corrections.db`:
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1. **Initialize** (first time): `uv run scripts/fix_transcription.py --init`
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2. **Add domain corrections**: `--add "错误词" "正确词" --domain <domain>`
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3. **Process transcript**: `--input file.md --stage 3`
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4. **Review learned patterns**: `--review-learned` and `--approve` high-confidence suggestions
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**Stages**: Dictionary (instant, free) → AI via GLM API (parallel) → Full pipeline
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**Domains**: `general`, `embodied_ai`, `finance`, `medical` (isolates corrections)
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**Learning**: Patterns appearing ≥3 times at ≥80% confidence move from AI to dictionary
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See `references/workflow_guide.md` for detailed workflows, `references/script_parameters.md` for complete CLI reference, and `references/team_collaboration.md` for collaboration patterns.
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## Bundled Resources
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**Scripts:**
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- `fix_transcript_enhanced.py` - Enhanced wrapper (recommended for interactive use)
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- `fix_transcription.py` - Core CLI (for automation)
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- `examples/bulk_import.py` - Bulk import example
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**References** (load as needed):
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- Getting started: `installation_setup.md`, `glm_api_setup.md`, `workflow_guide.md`
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- Daily use: `quick_reference.md`, `script_parameters.md`, `dictionary_guide.md`
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- Advanced: `sql_queries.md`, `file_formats.md`, `architecture.md`, `best_practices.md`
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- Operations: `troubleshooting.md`, `team_collaboration.md`
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## Troubleshooting
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Verify setup health with `uv run scripts/fix_transcription.py --validate`. Common issues:
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- Missing database → Run `--init`
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- Missing API key → `export GLM_API_KEY="<key>"` (obtain from https://open.bigmodel.cn/)
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- Permission errors → Check `~/.transcript-fixer/` ownership
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See `references/troubleshooting.md` for detailed error resolution and `references/glm_api_setup.md` for API configuration.
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