MuseNet Description
We have developed MuseNet, an advanced deep neural network capable of producing 4-minute musical pieces featuring 10 distinct instruments, while seamlessly merging genres ranging from country to the classical compositions of Mozart and even the iconic sounds of the Beatles. Rather than being programmed with musical knowledge, MuseNet identifies and learns patterns of harmony, rhythm, and style through the process of predicting the subsequent token in a vast collection of MIDI files. This innovative model employs the same unsupervised technology as GPT-2, a robust transformer model designed to anticipate the next token in a sequence, whether it pertains to audio or text. Thanks to MuseNet's understanding of diverse musical styles, we are able to create unique blends of musical generations. We eagerly anticipate the creative ways in which both musicians and those without formal training will leverage MuseNet to craft original compositions! Users can select a composer or style and optionally begin with a well-known piece, allowing them to delve into the rich array of musical styles that the model can produce. This opens up exciting possibilities for artistic exploration and experimentation.
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LTX Studio
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OpenAI Jukebox
We are excited to unveil Jukebox, a cutting-edge neural network designed to create music, including basic vocalization, in diverse genres and artistic expressions as raw audio. Alongside the release of the model weights and code, we are offering a tool to help users explore the music samples generated by Jukebox. By inputting genre, artist, and lyrics, users can receive entirely new music pieces crafted from the ground up. Jukebox is capable of producing a vast array of musical and vocal styles, and it can also generalize to lyrics that were not part of the training dataset. The lyrics included here have been collaboratively crafted by researchers at OpenAI and a language model. When provided with lyrics from its training set, Jukebox generates songs that diverge significantly from the originals, showcasing its creative capabilities. Users can input a 12-second audio clip for Jukebox to build upon, with the final output reflecting a desired style. Our focus on music stems from a desire to advance the potential of generative models further. Utilizing a quantization-based approach called VQ-VAE, Jukebox’s autoencoder model effectively compresses audio into a discrete latent space, enabling innovative sound generation. As we continue to refine these technologies, we look forward to the creative possibilities that lie ahead.
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Mureka
Mureka is a cutting-edge platform fueled by artificial intelligence, aimed at transforming the creative journey for songwriters and musicians alike. Integrating sophisticated AI technology with a user-friendly interface, Mureka enables users to effortlessly produce lyrics, melodies, and chord progressions that align with their unique artistic expression. The platform accommodates a wide array of musical genres and styles, providing creators with the flexibility to tailor their compositions and explore various concepts without difficulty. Additionally, Mureka features tools that facilitate real-time collaboration and brainstorming, empowering both beginners and seasoned artists to develop original pieces with remarkable ease and productivity. By bridging the gap between creativity and technology, Mureka not only enhances the music-making process but also fosters inspiration and accessibility for all aspiring musicians. Ultimately, this platform is set to redefine how music is created and experienced in the modern era.
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Pricing
Free Trial:
Yes
Company Details
Company:
OpenAI
Year Founded:
2015
Headquarters:
United States
Website:
openai.com/blog/musenet/
Media
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Webinars
Training Videos
Customer Support
Online Support
MuseNet Features and Options
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