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Endel is a personalized soundscape tool designed to help users focus, relax, and sleep. It uses patented technology to create soundscapes that adapt in real-time, reacting to inputs like time of day, weather, heart rate, and location. Endel has been shown to consistently improve focus and lower stress, and has partnered with Sony and Grammy Award-winning musicians to provide users with an even more immersive experience.
eMastered is an online mastering engine that uses artificial intelligence to help music creators improve the sound of their tracks. It provides users with a range of features such as Reference Mastering, Advanced Mastering Options, Cloud Storage, Shareable Library Page, Track Statistics, and more. It also offers a 14-day money back guarantee, making it an affordable and reliable option for quickly and easily mastering tracks.
RipX is a tool for removing vocals, creating stems, learning and practicing songs, remixing tracks and fixing audio. It offers a 21-day free trial and features such as DeepRemix, DeepCreate and DeepAudio. It also has features for customizing the look and feel of the tool. It is designed to provide users with a powerful and easy to use solution for audio processing.
Songburst is a powerful AI song maker designed for everyone. With it, users can create music for their online content such as videos and podcasts, generate samples to use in their own mixes, or export their songs to Spotify and Apple Music. The tool allows users to turn their words into music by describing the sound they want and AI will generate their own original track. Users can also use the Songburst Prompt Enhancer to make their prompt more descriptive and download their songs as wav or mp3 files with no limits. Additionally, the tool is available on both web and Android devices with a download available through the App Store.
MuseNet is a deep neural network created by OpenAI that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles. It uses the same general-purpose unsupervised technology as GPT-2, a large-scale transformer model trained to predict the next token in a sequence, whether audio or text. The model is trained on data from MIDI files and can generate samples in a chosen style by starting with a prompt. It uses several embeddings such as positional embeddings, a timing embedding, and structural embeddings to give the model more context.