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Average Ratings 2 Ratings
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.
Description
StaffPad is a highly acclaimed music notation application specifically crafted for touch and pen input, tailored for the needs of composers. This innovative app allows users to effortlessly compose music using their handwriting, edit with touch capabilities, and listen to their compositions with stunningly realistic audio playback. Complementing this, StaffPad Reader serves as a free companion app for musicians, enabling real-time display of individual parts from a StaffPad score across various devices. Any modifications made in StaffPad are instantly reflected in each connected Reader, ensuring seamless synchronization of annotations and playback as long as there is a simple Wi-Fi connection. Together, these applications create an exceptionally user-friendly and powerful environment for both composition and live performance. The advanced algorithms utilized by StaffPad transform handwritten notes into impeccably typeset scores, while also providing assistance by automatically correcting stem directions, incorporating courtesy accidentals, and indicating when beats are missing or excessive. This combination not only enhances the compositional process but also streamlines collaboration among musicians.
API Access
Has API
API Access
Has API
Integrations
Microsoft Azure
OpenAI
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$89.99 one-time payment
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
OpenAI
Founded
2015
Country
United States
Website
openai.com/blog/musenet/
Vendor Details
Company Name
StaffPad
Founded
2013
Country
United Kingdom
Website
www.staffpad.net