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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

Screenshots View All

Screenshots View All

Integrations

Microsoft Azure
OpenAI

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

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