audio-transcribe-summarize

👤 q1lin570 📦 v1.0.1 ⭐ 4.5 ⬇️ 741 下載
🎨 設計多媒體 免費 🔑 需 API Key

📖 技能介紹

Audio/Video Transcription & Summarization

Transcribe audio/video files using the SenseASR API (api.senseaudio.cn), then summarize the content into structured notes.

{baseDir} refers to this skill's directory.

Prerequisites

  • Environment variable SENSEAUDIO_API_KEY configured (get your key at https://senseaudio.cn/platform/api-key)
  • Python 3.8+ with requests installed

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  • For large files (>10MB): ffmpeg installed for splitting(macOS: brew install ffmpeg,Windows: ffmpeg.org 下載並加入 PATH,Linux: apt install ffmpeg)

Quick Start

  1. Run the transcription script:
python {baseDir}/scripts/transcribe.py <audio_file> [--model sense-asr-pro] [--language zh] [--speakers] [--sentiment] [--translate en]
  1. The script outputs a transcript .txt file alongside the source file
  2. Read the transcript and generate a summary (see Summary Format below)

Workflow

Step 1: Assess the Audio File

Check file size and format:

  • Supported formats: wav, mp3, ogg, flac, aac, m4a, mp4
  • Max file size per request: 10MB
  • If file > 10MB, the script auto-splits using ffmpeg

Step 2: Choose the Right Model

Model Use When
sense-asr-lite Quick batch transcription, simple audio, cost-sensitive
sense-asr General transcription, need speaker separation or timestamps
sense-asr-pro High accuracy needed: meetings, interviews, complex audio
sense-asr-deepthink Noisy audio, dialects, heavy jargon, speech-to-clean-text

Default to sense-asr-pro for best quality.

Step 3: Transcribe

Run the transcription script. Key options:

# Basic transcription
python {baseDir}/scripts/transcribe.py recording.mp3

# Meeting with multiple speakers + emotion
python {baseDir}/scripts/transcribe.py meeting.wav \
  --model sense-asr-pro \
  --speakers --max-speakers 4 \
  --sentiment \
  --timestamps segment

# Transcribe and translate to English
python {baseDir}/scripts/transcribe.py lecture.mp3 \
  --model sense-asr \
  --translate en

Step 4: Summarize

After transcription, read the transcript file and produce a summary using the format below.

Summary Format

Generate summaries in this structure:

# [Title - inferred from content]

**Source**: filename.mp3
**Duration**: X min Y sec
**Date**: YYYY-MM-DD
**Speakers**: [if speaker diarization was used]

## Key Points
- Point 1
- Point 2
- ...

## Detailed Summary
[2-4 paragraph summary of the content organized by topic/chronology]

## Action Items
- [ ] Action item 1 (assigned to Speaker X, if applicable)
- [ ] Action item 2

## Notable Quotes
> "Direct quote from transcript" — Speaker X, [timestamp if available]

## Full Transcript
<details>
<summary>Click to expand full transcript</summary>

[Full transcript text here, with speaker labels and timestamps if available]

</details>

Adapt the template based on content type:

  • Meeting: emphasize action items, decisions, speaker contributions
  • Lecture/Talk: emphasize key concepts, learning points, structure
  • Interview: emphasize Q&A pairs, key responses
  • Podcast: emphasize topics discussed, interesting insights

API Reference

For full SenseASR API parameters and response formats, see api-reference.md.

🤖 AI 評測

這個 Skill 質量良好,文件詳盡、功能全面,支援多種音訊格式和高階特性如說話人分離、情感分析、翻譯等。核心指令碼健壯可靠,能自動處理大檔案並適配多平臺環境。美中不足的是缺少示例檔案和使用教程,新手配置環境時可能遇到困難,另外也沒有測試保障程式碼穩定性。

📊 多維度評分

適應性4.3
規範性4.3
有效性4.3
可靠性4.6
可信度5

📁 包含檔案 (4 個)

📄 SKILL.md 3.6 KB
📄 _meta.json 145 B
📄 api-reference.md 3.4 KB
📄 scripts/transcribe.py 10.1 KB