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OpenAI Jukebox: How to Create Custom Songs with Neural Networks



How to Download and Use OpenAI Jukebox




Have you ever wondered how to create music with artificial intelligence? If so, you might be interested in OpenAI Jukebox, a neural network that can generate music in various genres and styles, including singing. In this article, we will show you how to download and use OpenAI Jukebox, as well as its limitations and alternatives.




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What is OpenAI Jukebox and what can it do?




OpenAI Jukebox is a project by OpenAI, a research organization that aims to create artificial intelligence that can benefit humanity. OpenAI Jukebox is a deep neural network that can generate music as raw audio, based on genre, artist, and lyrics as input. It can also imitate the voice of a particular singer, or blend different styles together. It can produce songs from scratch, or continue or re-render existing songs.


OpenAI Jukebox is powered by a large-scale transformer model that was trained on over a million songs in various genres and languages. It uses an autoencoder to compress raw audio into a lower-dimensional space, and then upsamples it back to the original space. It also uses a sparse transformer to model long-range dependencies in music.


OpenAI Jukebox is an impressive example of how artificial intelligence can learn to create music by discovering patterns of harmony, rhythm, and style. It can generate music that sounds realistic and diverse, as well as novel and creative. It can also capture human voices and emotions in singing.


How to download OpenAI Jukebox




If you want to try out OpenAI Jukebox for yourself, you will need to download it from its official website or GitHub repository. You will also need to install some dependencies and requirements before you can run it.


The official website of OpenAI Jukebox is [here](^1^). You can find the paper, blog post, code, samples, explorer tool, and colab notebook on this site. You can also listen to some curated samples of music generated by OpenAI Jukebox in different genres and styles.


The GitHub repository of OpenAI Jukebox is [here](^6^). You can find the source code, instructions, issues, pull requests, and license on this site. You can also clone or fork the repository to your own machine.


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To install OpenAI Jukebox, you will need the following requirements:


- Python 3.7.5 or higher - PyTorch 1.4 or higher - CUDA 10.0 or higher - MPI4Py 3.0.3 or higher - AV 7.0.01 or higher You can install these requirements using conda or pip commands. You will also need to install the jukebox package using pip install -e . command in the jukebox directory.


To run OpenAI Jukebox, you will need to use the jukebox/sample.py script. You can use different commands to sample from different models and modes. For example:



# To sample from scratch using the 5b_lyrics model python jukebox/sample.py --model=5b_lyrics --name=sample_5b --levels=3 --sample_length_in_seconds=20 \ --total_sample_length_in_seconds=180 --sr=44100 --n_samples=6 --hop_fraction=0.5,0.5,0.125 # To sample # To sample from a given genre using the 1b_lyrics model python jukebox/sample.py --model=1b_lyrics --name=sample_1b --levels=3 --sample_length_in_seconds=20 \ --total_sample_length_in_seconds=180 --sr=44100 --n_samples=6 --hop_fraction=0.5,0.5,0.125 \ --genre=hiphop # To sample from a given artist using the 5b model python jukebox/sample.py --model=5b --name=sample_5b_artist --levels=3 --sample_length_in_seconds=20 \ --total_sample_length_in_seconds=180 --sr=44100 --n_samples=6 --hop_fraction=0.5,0.5,0.125 \ --artist=Lady Gaga # To sample from a given lyrics using the 5b_lyrics model python jukebox/sample.py --model=5b_lyrics --name=sample_5b_lyrics --levels=3 --sample_length_in_seconds=20 \ --total_sample_length_in_seconds=180 --sr=44100 --n_samples=6 --hop_fraction=0.5,0.5,0.125 \ --lyrics="I'm on the edge of glory" # To continue an existing song using the 5b model python jukebox/sample.py --model=5b --name=sample_5b_continue --levels=3 --sample_length_in_seconds=20 \ --total_sample_length_in_seconds=180 --sr=44100 --n_samples=6 --hop_fraction=0.5,0.5,0.125 \ --mode=continue --audio_file=path/to/song.wav # To re-render an existing song using the 5b model python jukebox/sample.py --model=5b --name=sample_5b_rerender --levels=3 --sample_length_in_seconds=20 \ --total_sample_length_in_seconds=180 --sr=44100 --n_samples=6 --hop_fraction=0.5,0.5,0.125 \ --mode=rerender --audio_file=path/to/song.wav


You can find more details and examples of the commands in the README file of the GitHub repository.


How to use OpenAI Jukebox




Once you have downloaded and installed OpenAI Jukebox, you can start using it to generate music in various ways. You can choose from different models and modes, depending on your preferences and goals.


The models available are:


- 1b: A smaller model with 1 billion parameters that can generate music in 10 genres and 10 artists per genre. - 1b_lyrics: A variant of the 1b model that can also generate lyrics conditioned on genre and artist. - 5b: A larger model with 5 billion parameters that can generate music in over 6000 genres and artists. - 5b_lyrics: A variant of the 5b model that can also generate lyrics conditioned on genre and artist. The modes available are:


- ancestral: A mode that generates music by sampling from the prior distribution of the model, without any conditioning or input. - primed: A mode that generates music by sampling from the conditional distribution of the model, given some input parameters such as genre, artist, lyrics, or audio. - continue: A mode that generates music by continuing an existing song, given its audio file as input. - rerender: A mode that generates music by re-rendering an existing song, given its audio file as input. The input parameters and options are:


- genre: A parameter that specifies the genre of the music to be generated, such as rock, pop, jazz, etc. - artist: A parameter that specifies the artist of the music to be generated, such as Beatles, Taylor Swift, Frank Sinatra, etc. - lyrics: A parameter that specifies the lyrics of the music to be generated, as a string or a text file. - audio_file: A parameter that specifies the audio file of an existing song to be continued or re-rendered. - prompt_length_in_seconds: An option that specifies how long the input audio or lyrics should be used to prime the model. - sample_length_in_seconds: An option that specifies how long each sample of music should be generated. - total_sample_length_in_seconds: An option that specifies how long the total output of music should be generated. - sr: An option that specifies the sampling rate of the audio in Hz. - n_samples: An option that specifies how many samples of music should be generated for each input. - hop_fraction: An option that specifies how much overlap there should be between different levels of the model. The output formats and quality are:The output formats and quality are:


- .wav: A format that stores the raw audio data as waveforms, without any compression or encoding. This format preserves the highest quality and fidelity of the music, but also takes up more space and bandwidth. - .mp3: A format that compresses and encodes the audio data using a lossy algorithm that reduces the file size and bandwidth, but also introduces some distortion and noise. This format sacrifices some quality and fidelity of the music, but also saves more space and bandwidth. - .mid: A format that stores the musical notes and instructions as MIDI messages, without any audio data. This format allows the music to be played by different synthesizers and instruments, but also depends on their quality and compatibility. The quality of the music generated by OpenAI Jukebox depends on several factors, such as the model size, the input parameters, the sampling rate, the hop fraction, and the random seed. Generally, larger models produce better quality music, but also require more computational resources and time. Higher sampling rates and lower hop fractions produce higher fidelity music, but also increase the file size and bandwidth. Different input parameters and random seeds produce different variations of music, but also introduce some uncertainty and diversity.


Limitations and alternatives of OpenAI Jukebox




While OpenAI Jukebox is a remarkable achievement of artificial intelligence, it is not perfect or flawless. It has some limitations and challenges that need to be addressed and overcome.


Some of the limitations and challenges are:


- Computational cost: Generating music with OpenAI Jukebox requires a lot of computational power and memory, especially for the larger models. It can take hours or days to generate a few minutes of music on a single GPU or CPU. It can also consume a lot of electricity and generate a lot of heat. - Legal and ethical issues: Generating music with OpenAI Jukebox raises some legal and ethical questions about the ownership, rights, and responsibilities of the music. It can also create some conflicts and disputes between the original artists, the AI creators, and the AI users. - Musical quality and creativity: Generating music with OpenAI Jukebox does not guarantee that the music will be good or original. It can also produce some errors or artifacts that sound unnatural or unpleasant. It can also lack some human elements or emotions that make music more expressive or meaningful. If you are looking for some alternatives to OpenAI Jukebox, you can try some other software or tools that can create music with artificial intelligence. Some of them are:


- Amper Music: A software that can create custom music for videos, games, podcasts, etc., based on mood, style, length, etc. - AIVA: A software that can create original music for various purposes, such as film scoring, advertising, education, etc. - Magenta: A project by Google that can create music using deep learning and reinforcement learning algorithms. - Jukedeck: A software that can create royalty-free music for videos, games, podcasts, etc., based on genre, mood, tempo, etc. Conclusion




In this article, we have shown you how to download and use OpenAI Jukebox, a neural network that can generate music in various genres and styles, including singing. We have also discussed its limitations and alternatives.


OpenAI Jukebox is an amazing example of how artificial intelligence can learn to create music by discovering patterns of harmony, rhythm, and style. It can generate music that sounds realistic and diverse, as well as novel and creative. It can also capture human voices and emotions in singing.


If you are interested in creating music with artificial intelligence, you should definitely give OpenAI Jukebox a try. You might be surprised by what it can do. You might also discover some new genres or artists that you like.


So what are you waiting for? Download OpenAI Jukebox today and start making some music!


FAQs




Here are some frequently asked questions about OpenAI Jukebox:



  • What is OpenAI Jukebox?



OpenAI Jukebox is a neural network that can generate music in various genres and styles, including singing.


  • How to download OpenAI Jukebox?



You can download OpenAI Jukebox from its official website or GitHub repository. You will also need to install some dependencies and requirements before you can run it.


  • How to use OpenAI Jukebox?



You can use OpenAI Jukebox to generate music from scratch or from existing songs, using different models and modes. You can also specify some input parameters such as genre, artist , lyrics, or audio.


  • What are the limitations and alternatives of OpenAI Jukebox?



OpenAI Jukebox has some limitations and challenges, such as computational cost, legal and ethical issues, and musical quality and creativity. There are also some other software and tools that can create music with artificial intelligence, such as Amper Music, AIVA, Magenta, and Jukedeck.


  • How to cite OpenAI Jukebox?



If you want to cite OpenAI Jukebox in your academic or professional work, you can use the following format:



@articledhariwal2020jukebox, title=Jukebox: A Generative Model for Music, author=Dhariwal, Prafulla and Jun, Heewoo and Payne, Christine and Kim, Jong Wook and Radford, Alec and Sutskever, Ilya, journal=arXiv preprint arXiv:2005.00341, year=2020


  • Where to find more information and help about OpenAI Jukebox?



You can find more information and help about OpenAI Jukebox on its official website, GitHub repository, paper, blog post, colab notebook, explorer tool, and samples. You can also join the OpenAI community forum or Discord server to ask questions, share feedback, or collaborate with other users.


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