Musenet (OpenAI)
Pricing model
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MuseNet, developed by OpenAI, is a sophisticated neural network capable of creating 4-minute musical pieces using 10 different instruments and blending styles ranging from country to Mozart to the Beatles. It operates with the same versatile unsupervised technology as GPT-2, a vast transformer model designed to forecast the next token in a sequence, applicable to both audio and text. The model learns from MIDI file data and can produce samples in a selected style by beginning with a prompt. It utilizes multiple embeddings, including positional, timing, and structural embeddings, to provide the model with additional context.
Similar neural networks:
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Mixit is a mobile app that empowers users to craft unique cover versions of their preferred songs. Utilizing AI technology, it offers features such as an advanced lyrics generator and a music style swapper, allowing users to tailor songs and create fresh content. Users might be inclined to use Mixit for singing practice, generating music for social media sites such as TikTok and Instagram, or simply for the enjoyment of creatively reinterpreting songs in various genres. Its charm lies in its intuitive tools, enabling music lovers to unleash their creativity and share their versions with a wider audience.
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Sonauto seems to be an online platform where users can create, share, and explore songs. Participants can engage by developing their own music projects, sharing content, and offering feedback within a community of music enthusiasts. The platform includes a ranking system for songs, with categories like Popular Songs, New, Top of All Time, Top of Week, and Top of Day, so users can identify what’s trending. Individuals might be drawn to Sonauto to explore their musical creativity, gain inspiration, share their work with an audience, and connect with fellow musicians and music fans. This tool could be particularly valuable for aspiring songwriters, producers aiming to showcase their creations, or anyone interested in the collaborative and social dimensions of music creation and enjoyment.
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MusicLM is a model designed to create high-quality music from text descriptions. This tool employs a hierarchical sequence-to-sequence modeling approach, producing music at 24 kHz that maintains consistency over multiple minutes. It can tailor the generated music to both text and melody, enabling the transformation of whistled and hummed tunes into a style outlined in a text description. Moreover, the tool can produce music based on descriptions of paintings, various instruments, genres, musician experience levels, locations, and time periods. It is also capable of creating diverse versions of the same text prompt and semantic tokens.