Doubao Asr banner
vahnxu vahnxu

Doubao Asr

Development community

Description

Agent Skill: Transcribe audio files via ByteDance Volcengine Seed-ASR 2.0 (豆包录音文件识别模型2.0). Best-in-class Chinese speech recognition with step-by-step setup guide.

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

doubao-asr

Agent Skill for transcribing audio files via ByteDance Volcengine **Seed-ASR 2.0** (豆包录音文件识别模型2.0)

Best-in-class Chinese speech recognition — Mandarin, Cantonese, Sichuan dialect, and 13+ languages. With speaker diarization, SRT subtitle export, and three recognition tiers (standard / express / offpeak), up to 5 hours / 512MB per file.

中文语音识别准确率业界领先——支持普通话、粤语、四川话等方言及 13+ 种语言。自带说话人分离、SRT 字幕导出、三档识别版本(标准/极速/闲时),单文件最长 5 小时 / 512MB。

Why this skill?

Setting up Volcengine's Doubao Audio File Recognition 2.0 (豆包录音文件识别模型2.0, recorded audio → text) from scratch involves **4 environment variables across 3 different console pages** (Speech console, IAM, TOS). Without guidance, this typically takes 1-2 hours of doc-hunting and trial-and-error.

This skill provides **step-by-step bilingual setup instructions** (中英双语) baked into `SKILL.md`, so your AI agent can walk you through the entire process in ~10 minutes.

从零配置火山引擎豆包录音文件识别模型2.0(录音转文字)涉及 **3 个不同控制台页面的 4 个环境变量**。没有引导的话通常需要 1-2 小时翻文档踩坑。本 skill 在 `SKILL.md` 中内置了**中英双语分步引导**,AI agent 可以在约 10 分钟内带你完成全部配置。

Install

Claude Code

claude /install-skill https://github.com/vahnxu/doubao-asr

Or manually copy to `~/.claude/skills/doubao-asr/`.

OpenClaw / ClawHub

Available on [ClawHub](https://clawhub.com) as `doubao-asr`.

Manual

git clone https://github.com/vahnxu/doubao-asr.git
cd doubao-asr
pip install requests
python3 scripts/transcribe.py /path/to/audio.m4a

Quick start

# Basic transcription
python3 scripts/transcribe.py /path/to/audio.m4a

# Save to file
python3 scripts/transcribe.py /path/to/audio.m4a --out /tmp/transcript.txt

# JSON output
python3 scripts/transcribe.py /path/to/audio.m4a --json --out /tmp/result.json

# Direct URL (skip upload)
python3 scripts/transcribe.py https://example.com/audio.mp3

# Disable speaker diarization
python3 scripts/transcribe.py /path/to/audio.m4a --no-speakers

# Export SRT subtitles (from per-utterance timestamps)