UltraSinger

⚠️ This project is still under development!

UltraSinger is a tool to automatically create UltraStar.txt, midi and notes from music. It automatically pitches UltraStar files, adding text and tapping to UltraStar files and creates separate UltraStar karaoke files. It also can re-pitch current UltraStar files and calculates the possible in-game score.

Multiple AI models are used to extract text from the voice and to determine the pitch.

Please mention UltraSinger in your UltraStar.txt file if you use it. It helps others find this tool, and it helps this tool get improved and maintained. You should only use it on Creative Commons licensed songs.

❤️ Support

There are many ways to support this project. Starring ⭐️ the repo is just one 🙏

You can also support this work on GitHub sponsors or Patreon or Buy Me a Coffee.

This will help me a lot to keep this project alive and improve it.

Table of Contents

• UltraSinger
  • ❤️ Support
  • Table of Contents
  • 💻 How to use this source code
    • Installation
    • Run
  • 📖 How to use the App
    • 🎶 Input
      • Audio (full automatic)
        • Local file
        • Youtube
      • UltraStar (re-pitch)
    • 🗣 Transcriber
      • Whisper
        • Whisper languages
      • ✍️ Hyphenation
    • 👂 Pitcher
    • 👄 Separation
    • Sheet Music
    • Format Version
    • 🏆 Ultrastar Score Calculation
    • 📟 Use GPU
      • Considerations for Windows users
      • Info
      • Docker

💻 How to use this source code

Installation

• Install Python 3.10 (older and newer versions has some breaking changes). Download
• Also install ffmpeg separately with PATH. Download
• Go to folder install and run install script for your OS.
  • Choose GPU if you have an nvidia CUDA GPU.
  • Choose CPU if you don't have an nvidia CUDA GPU.

Run

• In root folder just run run_on_windows.bat or run_on_linux.sh to start the app.
• Now you can use the UltraSinger source code with py UltraSinger.py [opt] [mode] [transcription] [pitcher] [extra]. See How to use for more information.

📖 How to use the App

Not all options working now!

    UltraSinger.py [opt] [mode] [transcription] [pitcher] [extra]
    
    [opt]
    -h      This help text.
    -i      Ultrastar.txt
            audio like .mp3, .wav, youtube link
    -o      Output folder
    
    [mode]
    ## if INPUT is audio ##
    default  Creates all
    
    # Single file creation selection is in progress, you currently getting all!
    (-u      Create ultrastar txt file) # In Progress
    (-m      Create midi file) # In Progress
    (-s      Create sheet file) # In Progress
    
    ## if INPUT is ultrastar.txt ##
    default  Creates all

    # Single selection is in progress, you currently getting all!
    (-r      repitch Ultrastar.txt (input has to be audio)) # In Progress
    (-p      Check pitch of Ultrastar.txt input) # In Progress
    (-m      Create midi file) # In Progress

    [transcription]
    # Default is whisper
    --whisper               Multilingual model > tiny|base|small|medium|large-v1|large-v2  >> ((default) is large-v2
                            English-only model > tiny.en|base.en|small.en|medium.en
    --whisper_align_model   Use other languages model for Whisper provided from huggingface.co
    --language              Override the language detected by whisper, does not affect transcription but steps after transcription
    --whisper_batch_size    Reduce if low on GPU mem >> ((default) is 16)
    --whisper_compute_type  Change to "int8" if low on GPU mem (may reduce accuracy) >> ((default) is "float16" for cuda devices, "int8" for cpu)
    
    [pitcher]
    # Default is crepe
    --crepe            tiny|full >> ((default) is full)
    --crepe_step_size  unit is miliseconds >> ((default) is 10)
    
    [extra]
    --hyphenation           True|False >> ((default) is True)
    --disable_separation    True|False >> ((default) is False)
    --disable_karaoke       True|False >> ((default) is False)
    --ignore_audio          True|False >> ((default) is False)
    --create_audio_chunks   True|False >> ((default) is False)
    --keep_cache            True|False >> ((default) is False)
    --plot                  True|False >> ((default) is False)
    --format_version        0.3.0|1.0.0|1.1.0 >> ((default) is 1.0.0)
    --musescore_path        path to MuseScore executable

    [device]
    --force_cpu             True|False >> ((default) is False)  All steps will be forced to cpu
    --force_whisper_cpu     True|False >> ((default) is False)  Only whisper will be forced to cpu
    --force_crepe_cpu       True|False >> ((default) is False)  Only crepe will be forced to cpu

For standard use, you only need to use [opt]. All other options are optional.

🎶 Input

Audio (full automatic)

Local file

-i "input/music.mp3"

Youtube

-i https://www.youtube.com/watch?v=BaW_jenozKc

UltraStar (re-pitch)

This re-pitch the audio and creates a new txt file.

-i "input/ultrastar.txt"

🗣 Transcriber

Keep in mind that while a larger model is more accurate, it also takes longer to transcribe.

Whisper

For the first test run, use the tiny, to be accurate use the large-v2 model.

-i XYZ --whisper large-v2

Whisper languages

Currently provided default language models are en, fr, de, es, it, ja, zh, nl, uk, pt. If the language is not in this list, you need to find a phoneme-based ASR model from 🤗 huggingface model hub. It will download automatically.

Example for romanian:

-i XYZ --whisper_align_model "gigant/romanian-wav2vec2"

✍️ Hyphenation

Is on by default. Can also be deactivated if hyphenation does not produce anything useful. Note that the word is simply split, without paying attention to whether the separated word really starts at the place or is heard.

-i XYZ --hyphenation True

👂 Pitcher

Pitching is done with the crepe model. Also consider that a bigger model is more accurate, but also takes longer to pitch. For just testing you should use tiny. If you want solid accurate, then use the full model.

-i XYZ --crepe full

👄 Separation

The vocals are separated from the audio before they are passed to the models. If problems occur with this, you have the option to disable this function; in which case the original audio file is used instead.

-i XYZ --disable_separation True

Sheet Music

For Sheet Music generation you need to have MuseScore installed on your system. Or provide the path to the MuseScore executable.

-i XYZ --musescore_path "C:/Program Files/MuseScore 4/bin/MuseScore4.exe"

Format Version

This defines the format version of the UltraStar.txt file. For more info see Official UltraStar format specification.

You can choose between 3 different format versions. The default is 1.0.0.

• 0.3.0 is the old format version. Use this if you have problems with the new format.
• 1.0.0 is the current format version.
• 1.1.0 is the upcoming format version. It is not finished yet.

-i XYZ --format_version 1.0.0

🏆 Ultrastar Score Calculation

The score that the singer in the audio would receive will be measured. You get 2 scores, simple and accurate. You wonder where the difference is? Ultrastar is not interested in pitch hights. As long as it is in the pitch range A-G you get one point. This makes sense for the game, because otherwise men don't get points for high female voices and women don't get points for low male voices. Accurate is the real tone specified in the txt. I had txt files where the pitch was in a range not singable by humans, but you could still reach the 10k points in the game. The accuracy is important here, because from this MIDI and sheet are created. And you also want to have accurate files

📟 Use GPU

With a GPU you can speed up the process. Also the quality of the transcription and pitching is better.

You need a cuda device for this to work. Sorry, there is no cuda device for macOS.

It is optional (but recommended) to install the cuda driver for your gpu: see driver. Install torch with cuda separately in your venv. See tourch+cuda. Also check you GPU cuda support. See cuda support

Command for pip:

pip3 install torch==2.0.1+cu117 torchvision==0.15.2+cu117 torchaudio==2.0.2+cu117 --index-url https://download.pytorch.org/whl/cu117

When you want to use conda instead you need a different installation command.

Considerations for Windows users

The pitch tracker used by UltraSinger (crepe) uses TensorFlow as its backend. TensorFlow dropped GPU support for Windows for versions >2.10 as you can see in this release note and their installation instructions.

For now UltraSinger runs the latest version available that still supports GPUs on windows.

For running later versions of TensorFlow on windows while still taking advantage of GPU support the suggested solution is:

• install WSL2
• within the Ubuntu WSL2 installation
  • run sudo apt update && sudo apt install nvidia-cuda-toolkit
  • follow the setup instructions for UltraSinger at the top of this document

Info

If something crashes because of low VRAM then use a smaller model. Whisper needs more than 8GB VRAM in the large model!

You can also force cpu usage with the extra option --force_cpu.

Docker

to run the docker run git clone https://github.com/rakuri255/UltraSinger.git enter the UltraSinger folder. run this command to build the docker docker build -t ultrasinger . make sure to include the "." at the end let this run till complete. then run this command docker run --gpus all -it --name UltraSinger -v $pwd/src/output:/app/src/output ultrasinger

Docker-Compose there are two files that you can pick from. cd into docker-compose folder and then cd into Nvidia or NonGPU Run docker-compose up to download and setup

Nvidia is for if you have a nvidia gpu to use with UltraSinger. NonGPU is for if you wish to only use the CPU for UltraSinger.

Output by default the docker-compose will setup the output folder as /output inside the docker. on the host machine it will map to the folder with the docker-compose.yml file under output you may chnage this by editing the docker-compose.yml

to edit the file. use any text editor you wish. i would recoment nano. run nano docker-compose.yml then change this line - ./output:/app/UltraSinger/src/output to anything you line for on your host machine. - /yourfolderpathhere:/app/UltraSinger/src/output sample - /mnt/user/appdata/UltraSinger:/output note the blank space before the - formating is important here in this file.

this will create and drop you into the docker. now run this command. python3 UltraSinger.py -i file or python3 UltraSinger.py -i youtube_url to use mp3's in the folder you git cloned you must place all songs you like in UltraSinger/src/output. this will be the place for youtube links aswell.

to quit the docker just type exit.

to reenter docker run this command docker start UltraSinger && Docker exec -it UltraSinger /bin/bash