songtrace

Self-hosted karaoke chart builder for UltraStar and compatible games such as Melody Mania. Give it a song's video and lyrics and it charts the notes, timing and pitch, ready for your collection. Fix anything in the built-in editor; your edits survive when you rebuild your whole collection after a songtrace update.

What it does

You give it a title, artist, the lyrics, and a YouTube URL or a video file. songtrace writes a song folder (.txt chart, .mp3, video and cover) into your collection:

1. acquire: downloads the video with yt-dlp, or takes your file
2. separate: splits vocals from the backing track (Demucs)
3. transcribe: has your Whisper server transcribe the vocals, to check the lyrics match the recording and to find where the singing is
4. align: places each word of your lyrics on the vocals (wav2vec2)
5. pitch: tracks the sung pitch (torchcrepe)
6. notes: turns word timings and pitch into notes
7. grid: snaps the notes to a beat grid
8. package: writes the song folder

The result is a strong draft, not a finished chart. The web UI flags the notes it is least sure of, plays the song back against the chart, and lets you fix what it got wrong before you sing it.

Requirements

• An NVIDIA GPU with CUDA. songtrace is developed on a 12 GB card. Separating the vocals (Demucs) alone takes about 3.7 GB, and alignment holds a whole stretch of singing in memory at once, so a long song whose vocals never pause needs the most. Cards under 12 GB are untested. Each stage gives the GPU back when it finishes (see Sharing the GPU). device = "cpu" in the config runs without a GPU, but it is untested, far slower, and needs plenty of system RAM.
• Docker with the NVIDIA Container Toolkit, so the container can see the GPU.
• A Whisper server of your own. songtrace does not include one. Either an OpenAI-compatible API or whisper-asr-webservice works. If it shares songtrace's GPU, it needs its own share of the memory.
• Disk space: a few GB of model weights, downloaded on first use, plus a working folder per song holding its source video and separated tracks, typically several hundred MB.

Quick start (Docker)

cp config.example.toml config.toml
$EDITOR config.toml   # set whisper_url to your Whisper server
docker compose up -d --build

Open http://localhost:8000, fill in the form and press CREATE SONG. To update, git pull and run the same docker compose command again.

Finished songs go to output_dir (/data/output in the container). To write them straight into your game's song collection, mount that folder there in docker-compose.yml:

    volumes:
      - ./config.toml:/config/config.toml:ro
      - ./data:/data
      - /path/to/your/UltraStar/songs:/data/output

Everything else lives under ./data on the host (model weights, and each song's working files), so it survives recreating the container.

Reviewing and editing a song

Pick a song in the queue. The review panel plays the packaged song with its video, highlights the line and words being sung, and shows the chart on a note sheet above the lyrics. Playback works like the game: the #MP3 is the clock and the video follows it muted, so a word that lights up late here is late in the game too.

The note sheet shows one line at a time on a pitch-by-beat grid, with the pitch songtrace detected drawn over the notes. Where a note is right the curve runs through it, so a wrong one stands out. Fix it there and SAVE LINE; the song's chart is rewritten on the spot.

• Notes: drag a note to move it, drag its ends to resize it. Everything snaps to the beat grid and to semitones. Double-click empty space to add a note, or a note to change its syllable. With the sheet focused, the arrow keys move notes, S splits, M merges, G/F/R make a note golden, freestyle or rap, Ctrl+Z undoes and Ctrl+S saves. Press ? for every shortcut.
• Line breaks: the ↵ markers either side of a line. Drag one to move it, and double-click it to hand it back to songtrace.
• Tempo: the GRID bar sets the chart's BPM and GAP. It redraws as you type and charts on APPLY. ×2 and ÷2 fix a tempo detected at double or half speed, and ALIGN TO NOTE puts the selected note on a beat. RESET goes back to songtrace's choice.
• Undoing an edit: REVERT returns a line to the generated notes.

Edits are kept apart from what the pipeline generates and laid back over it on every rebuild, so they survive all of them, collection-wide ones included. If you change a line's lyrics, its edit is set aside rather than applied to different words, and the sheet lists those for you to discard. Songs with edits are marked ✎ in the queue.

Rebuilding

Select a song and its inputs come back up in the form; change them and press REBUILD SONG. Only the stages your change affects are rerun: fixing a line of lyrics realigns without downloading or separating again.

A songtrace update can improve a stage without any of your inputs changing. Restart from on the rebuild form redoes a stage anyway, and REBUILD ALL FROM…, under CREATE SONG, does it for your whole collection: pick the stage the update improved, untick any songs to leave alone, and each song is rebuilt from there. Your edits are kept.

Stages in order: acquire, separate, transcribe, align, pitch, notes, grid, package. Rebuilding from notes onward needs no GPU.

Configuration

config.toml is TOML; config.example.toml lists every setting. songtrace reads, in order: --config <path>, the SONGTRACE_CONFIG environment variable (set to /config/config.toml in the container), then ~/.config/songtrace/config.toml.

whisper_api chooses how to talk to Whisper: "openai" (the default) uses POST {whisper_url}/audio/transcriptions, and "asr-webservice" uses whisper-asr-webservice's POST {whisper_url}/asr. For the latter, give whisper_url without a /v1 suffix; whisper_model and whisper_api_key are ignored, since that server's model is fixed when it starts.

creator sets the #CREATOR header in every chart; it defaults to songtrace.

Sharing the GPU

Three stages load a model: separate (Demucs), align (wav2vec2) and pitch (torchcrepe). Each releases its model and returns the memory to the driver as soon as it finishes, rather than holding it for the life of the server. This matters most while transcribe waits on your Whisper server, which can take minutes. The job log says how much each stage gave back:

[separate] released 3704 MiB of GPU memory

Reloading the models costs seconds per song. The CUDA context itself, a few hundred MB, stays with the process; stop the container to free it.

YouTube download failures

YouTube changes its defences every few weeks, so songtrace keeps yt-dlp current by itself. Once a day, and again when a download fails, it checks PyPI for a newer stable release, installs it under /data/models/cache, and tries it before the copy it shipped with. That copy is never modified and is always the fallback, so a broken release costs a retry, not the download. The job log names the yt-dlp version behind each attempt. ytdlp_version pins a release, or "bundled" turns the updates off.

If downloads still fail with HTTP Error 403: Forbidden:

1. The network is rate-limited or flagged. Datacenter and VPN ranges are throttled hardest. Try another network before changing config.
2. A PO token is required. If the log says so, run bgutil-ytdlp-pot-provider alongside songtrace, install its plugin into the image, and point ytdlp_pot_provider_url at it.
3. Other levers: ytdlp_clients tries each listed YouTube player client in turn. ytdlp_cookies takes a Netscape cookie jar for age-gated videos; don't use one from an account you care about, as YouTube bans automated access. ytdlp_impersonate presents a browser's TLS fingerprint (for example "chrome").

To check the JavaScript runtime yt-dlp needs for YouTube is present, run docker compose exec songtrace yt-dlp -v --simulate <url>; the JS runtimes: line must not say none. A failed download keeps its working folder, so running the job again resumes it.

Command line

The web UI is the main way to use songtrace, but every song can also be made from the command line, in the container or on a host with the requirements above and ffmpeg:

docker compose run --rm songtrace songtrace make \
  --title "Song Title" --artist "Artist Name" \
  --lyrics /data/lyrics.txt --youtube https://youtu.be/...

songtrace make --title TITLE --artist ARTIST --lyrics LYRICS_FILE \
  (--youtube URL | --video PATH) \
  [--genre GENRE] [--year YEAR] [--language LANGUAGE] [--cover COVER_IMAGE] \
  [--bpm BPM] [--force-from STAGE] [--config CONFIG]

--force-from <stage> redoes that stage and everything after it, reusing the cached output of the stages before. On a bare-metal host, install with pip install -e . and run the web UI with songtrace serve.

Development

pip install -e '.[dev]'
pytest

pytest also runs the web UI's JavaScript tests in tests/js when Node is installed. Pull requests run the full suite in CI.

songtrace is developed on a private forge and published to GitHub as a read-only mirror; see mirror/README.md.

scripts/screenshot_webui.py regenerates docs/images/webui.png from a seeded copy of the app (playwright install chromium first). With ffmpeg on PATH, the shot includes the player.

License

AGPLv3