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moss-transcribe-diarize

Comprehensive MOSS Transcribe Diarize workflow for high-confidence multi-speaker ASR. Use when users need (1) timestamped transcription, (2) speaker-labeled segments/diarization, (3) meeting or interview transcript extraction, or (4) ASR from URL/Base64/local audio-video files with structured post-processing outputs (raw JSON, segment timeline, and by-speaker summary).

helloeveryworlds0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install helloeveryworlds/moss-transcribe-diarize

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

MOSS Transcribe Diarize Skill

Call this skill when users want:

  • 多人语音转写(带说话人)
  • 带时间戳的会议纪要原文
  • 从音视频 URL / 本地文件做 ASR + diarization

Quick workflow

  1. 准备音频来源(URL / 本地文件 / Base64)
  2. 调用 scripts/transcribe.py
  3. 用 segments 生成:逐段文本、按说话人汇总、会后纪要

API assumptions (from docs page)

  • 模型名固定:moss-transcribe-diarize
  • 请求体核心字段:
    • audio_data(URL 或 data URL)
    • model
    • sampling_params(如 max_new_tokens, temperature)
    • meta_info(可选)
  • 返回中重点看:
    • text
    • meta_info
    • segments(含时间戳、speaker、content)

官方文档入口:https://studio.mosi.cn/docs/moss-transcribe-diarize

Run

# URL 音频
python scripts/transcribe.py \
  --audio-url "https://example.com/audio.mp3" \
  --api-key "$MOSS_API_KEY" \
  --out result.json

# 本地文件(自动转 data URL)
python scripts/transcribe.py \
  --file "/path/to/meeting.mp4" \
  --api-key "$MOSS_API_KEY" \
  --out result.json

Endpoint

默认 endpoint:https://studio.mosi.cn/v1/audio/transcriptions

如果你的环境 endpoint 不同,用参数覆盖:

--endpoint "https://your-endpoint"

Output handling

  • 原始结果保存为 JSON
  • 脚本会额外导出:
    • *.segments.txt(逐段)
    • *.by_speaker.txt(按说话人)

Source information

Source
github
Repository
openclaw/skills
Path
skills/helloeveryworlds/moss-transcribe-diarize
Version
—
Commit
ea4b2efd4c14759a05c98dfa9762b861a57503d1
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# MOSS Transcribe Diarize Skill

Call this skill when users want:
- 多人语音转写(带说话人)
- 带时间戳的会议纪要原文
- 从音视频 URL / 本地文件做 ASR + diarization

## Quick workflow

1. 准备音频来源(URL / 本地文件 / Base64)
2. 调用 `scripts/transcribe.py`
3. 用 `segments` 生成:逐段文本、按说话人汇总、会后纪要

## API assumptions (from docs page)
- 模型名固定:`moss-transcribe-diarize`
- 请求体核心字段:
  - `audio_data`(URL 或 data URL)
  - `model`
  - `sampling_params`(如 `max_new_tokens`, `temperature`)
  - `meta_info`(可选)
- 返回中重点看:
  - `text`
  - `meta_info`
  - `segments`(含时间戳、speaker、content)

> 官方文档入口:`https://studio.mosi.cn/docs/moss-transcribe-diarize`

## Run

```bash
# URL 音频
python scripts/transcribe.py \
  --audio-url "https://example.com/audio.mp3" \
  --api-key "$MOSS_API_KEY" \
  --out result.json

# 本地文件(自动转 data URL)
python scripts/transcribe.py \
  --file "/path/to/meeting.mp4" \
  --api-key "$MOSS_API_KEY" \
  --out result.json
```

## Endpoint

默认 endpoint:`https://studio.mosi.cn/v1/audio/transcriptions`

如果你的环境 endpoint 不同,用参数覆盖:

```bash
--endpoint "https://your-endpoint"
```

## Output handling

- 原始结果保存为 JSON
- 脚本会额外导出:
  - `*.segments.txt`(逐段)
  - `*.by_speaker.txt`(按说话人)

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