Sonauto
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Pricing model
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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.
Similar neural networks:
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Vozart AI is a cutting-edge tool for generating music from text prompts, producing fully finished, royalty-free tracks in just minutes without needing any musical expertise. It manages every part of song production, from composition to mastering, enabling users to export in different formats and work together in real-time. This makes it a popular choice among content creators, songwriters, marketers, and educators who need custom music for projects, valuing its user-friendly approach, rapid production speed, and adaptable licensing that removes the usual obstacles in music creation, while granting complete commercial usage rights.
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Emvoice One is a vocal synthesis plugin designed for music producers and other creatives, allowing them to create lifelike vocal performances through text input. It features four distinct voices—Keela, Lucy, Jay, and Thomas—each with varying ranges and prices, and includes a free demo mode with restricted features. The plugin operates on both Mac and PC, requires an internet connection, and is compatible with VST/AU/AAX.
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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.