Acestep Lyrics Transcription logo

Acestep Lyrics Transcription

Organization
ace-step
acestep-lyrics-transcription

Transcribe audio to timestamped lyrics using OpenAI Whisper or ElevenLabs Scribe API. Outputs LRC, SRT, or JSON with word-level timestamps. Use when users want to transcribe songs, generate LRC files, or extract lyrics with timestamps from audio.

Overview

Publisherace-step
Repositoryace-step-skills
Skill nameacestep-lyrics-transcription
Stars
99
Forks
20
Bundled files
2
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ace-step on GitHub. Read the source before you install it.

Installation

Install the Acestep Lyrics Transcription AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ace-step/ace-step-skills/tree/main/skills/acestep-lyrics-transcription
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ace-step/ace-step-skills.git /tmp/ace-step-skills
mkdir -p .claude/skills
cp -r /tmp/ace-step-skills/skills/acestep-lyrics-transcription .claude/skills/acestep-lyrics-transcription
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Acestep Lyrics Transcription in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Acestep Lyrics Transcription on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Acestep Lyrics Transcription is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Lyrics Transcription Skill

Transcribe audio files to timestamped lyrics (LRC/SRT/JSON) via OpenAI Whisper or ElevenLabs Scribe API.

API Key Setup Guide

Before transcribing, you MUST check whether the user's API key is configured. Run the following command to check:

bash
cd "{project_root}/{.claude or .codex}/skills/acestep-lyrics-transcription/" && bash ./scripts/acestep-lyrics-transcription.sh config --check-key

This command only reports whether the active provider's API key is set or empty — it does NOT print the actual key value. NEVER read or display the user's API key content. Do not use config --get on key fields or read config.json directly. The config --list command is safe — it automatically masks API keys as *** in output.

If the command reports the key is empty, you MUST stop and guide the user to configure it before proceeding. Do NOT attempt transcription without a valid key — it will fail.

Use AskUserQuestion to ask the user to provide their API key, with the following options and guidance:

  1. Tell the user which provider is currently active (openai or elevenlabs) and that its API key is not configured. Explain that transcription cannot proceed without it.
  2. Provide clear instructions on where to obtain a key:
  3. Also offer the option to switch to the other provider if they already have a key for it.
  4. Once the user provides the key, configure it using:
    bash
    cd "{project_root}/{.claude or .codex}/skills/acestep-lyrics-transcription/" && bash ./scripts/acestep-lyrics-transcription.sh config --set <provider>.api_key <KEY>
  5. If the user wants to switch providers, also run:
    bash
    cd "{project_root}/{.claude or .codex}/skills/acestep-lyrics-transcription/" && bash ./scripts/acestep-lyrics-transcription.sh config --set provider <provider_name>
  6. After configuring, re-run config --check-key to verify the key is set before proceeding.

If the API key is already configured, proceed directly to transcription without asking.

Quick Start

bash
# 1. cd to this skill's directory
cd {project_root}/{.claude or .codex}/skills/acestep-lyrics-transcription/

# 2. Configure API key (choose one)
./scripts/acestep-lyrics-transcription.sh config --set openai.api_key sk-...
# or
./scripts/acestep-lyrics-transcription.sh config --set elevenlabs.api_key ...
./scripts/acestep-lyrics-transcription.sh config --set provider elevenlabs

# 3. Transcribe
./scripts/acestep-lyrics-transcription.sh transcribe --audio /path/to/song.mp3 --language zh

# 4. Output saved to: {project_root}/acestep_output/<filename>.lrc

Prerequisites

  • curl, jq, python3 (or python)
  • An API key for OpenAI or ElevenLabs

Script Usage

bash
./scripts/acestep-lyrics-transcription.sh transcribe --audio <file> [options]

Options:
  -a, --audio      Audio file path (required)
  -l, --language   Language code (zh, en, ja, etc.)
  -f, --format     Output format: lrc, srt, json (default: lrc)
  -p, --provider   API provider: openai, elevenlabs (overrides config)
  -o, --output     Output file path (default: acestep_output/<filename>.lrc)

Post-Transcription Lyrics Correction (MANDATORY)

CRITICAL: After transcription, you MUST manually correct the LRC file before using it for MV rendering. Transcription models frequently produce errors on sung lyrics:

  • Proper nouns: "ACE-Step" → "AC step", "Spotify" → "spot a fly"
  • Similar-sounding words: "arrives" → "eyes", "open source" → "open sores"
  • Merged/split words: "lighting up" → "lightin' nup"

Correction Workflow

  1. Read the transcribed LRC file using the Read tool
  2. Read the original lyrics from the ACE-Step output JSON file
  3. Use original lyrics as a whole reference: Do NOT attempt line-by-line alignment — transcription often splits, merges, or reorders lines differently from the original. Instead, read the original lyrics in full to understand the correct wording, then scan each LRC line and fix any misrecognized words based on your knowledge of what the original lyrics say.
  4. Fix transcription errors: Replace misrecognized words with the correct original words, keeping the timestamps intact
  5. Write the corrected LRC back using the Write tool

What to Correct

  • Replace misrecognized words with their correct original versions
  • Keep all [MM:SS.cc] timestamps exactly as-is (timestamps from transcription are accurate)
  • Do NOT add structure tags like [Verse] or [Chorus] — the LRC should only have timestamped text lines

Example

Transcribed (wrong):

[00:46.96]AC step alive,
[00:50.80]one point five eyes.

Original lyrics reference:

ACE-Step alive
One point five arrives

Corrected (right):

[00:46.96]ACE-Step alive,
[00:50.80]One point five arrives.

Configuration

Config file: scripts/config.json

bash
# Switch provider
./scripts/acestep-lyrics-transcription.sh config --set provider openai
./scripts/acestep-lyrics-transcription.sh config --set provider elevenlabs

# Set API keys
./scripts/acestep-lyrics-transcription.sh config --set openai.api_key sk-...
./scripts/acestep-lyrics-transcription.sh config --set elevenlabs.api_key ...

# View config
./scripts/acestep-lyrics-transcription.sh config --list
OptionDefaultDescription
provideropenaiActive provider: openai or elevenlabs
output_formatlrcDefault output: lrc, srt, or json
openai.api_key""OpenAI API key
openai.api_urlhttps://api.openai.com/v1OpenAI API base URL
openai.modelwhisper-1OpenAI model (whisper-1 for word timestamps)
elevenlabs.api_key""ElevenLabs API key
elevenlabs.api_urlhttps://api.elevenlabs.io/v1ElevenLabs API base URL
elevenlabs.modelscribe_v2ElevenLabs model

Provider Notes

ProviderModelWord TimestampsPricing
OpenAIwhisper-1Yes (segment + word)$0.006/min
ElevenLabsscribe_v2Yes (word-level)Varies by plan
  • OpenAI whisper-1 is the only OpenAI model supporting word-level timestamps
  • ElevenLabs scribe_v2 returns word-level timestamps with type filtering
  • Both support multilingual transcription

Examples

bash
# Basic transcription (uses config defaults)
./scripts/acestep-lyrics-transcription.sh transcribe --audio song.mp3

# Chinese song to LRC
./scripts/acestep-lyrics-transcription.sh transcribe --audio song.mp3 --language zh

# Use ElevenLabs, output SRT
./scripts/acestep-lyrics-transcription.sh transcribe --audio song.mp3 --provider elevenlabs --format srt

# Custom output path
./scripts/acestep-lyrics-transcription.sh transcribe --audio song.mp3 --output ./my_lyrics.lrc

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Acestep Lyrics Transcription AI skill do?

Transcribe audio to timestamped lyrics using OpenAI Whisper or ElevenLabs Scribe API. Outputs LRC, SRT, or JSON with word-level timestamps. Use when users want to transcribe songs, generate LRC files, or extract lyrics with timestamps from audio.

Why use Acestep Lyrics Transcription on TypingMind?

Because you install it once and use it with any model. Acestep Lyrics Transcription is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Acestep Lyrics Transcription in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ace-step/ace-step-skills/tree/main/skills/acestep-lyrics-transcription. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Acestep Lyrics Transcription?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Acestep Lyrics Transcription?

As many as you like. As long as a model supports skills, you can use Acestep Lyrics Transcription with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Acestep Lyrics Transcription AI skill free?

It is published on GitHub by ace-step. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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