ScoreCloud

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Freemium
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ScoreCloud is a music notation program that transforms music into sheet music, designed for musicians, students, teachers, choirs, bands, composers, and arrangers. It offers audio and MIDI transcription, robust editing tools, various output formats, and cross-device synchronization. The ScoreCloud Express mobile app for iPhone and iPad enables users to jot down musical ideas on the go by singing, whistling, or humming a tune or baseline into the app. Furthermore, ScoreCloud provides three subscription plans with different feature levels.

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Magenta Studio comprises a set of music plugins driven by Magenta's open-source tools and models. Utilizing machine learning techniques, these tools facilitate music creation and are accessible as both standalone applications and plugins for Ableton Live. Users can read and write clips in Ableton's Session View, as well as read and write files from their file system.
Freemium
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Cassette is an AI-driven music creation tool that allows users of any skill level to produce high-quality, royalty-free music tracks tailored to their specific needs and preferences. Built on a machine learning model based on latent diffusion (LDMs), it can envision beats using the text descriptions provided by users. Featuring an intuitive interface, users can enter various parameters such as desired genre, mood, length, and instrumentation, and CassetteAI will generate a full track from scratch. There is no ownership of the beats created by users, and the only limit to beat creation is the user's imagination.
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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.