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Description
Lyria 3.5 is the latest AI music generation model from Google DeepMind, engineered to assist users in crafting more intricate and high-quality tracks with enhanced musical and technical precision. Integrated into Google Flow Music, this model elevates musical creativity by offering more sophisticated and nuanced melodic patterns, as well as a deeper comprehension of rhythm, arrangement, tempo, dynamics, and acoustic subtleties. The improved lyric generation capabilities ensure better adherence to prompts and a heightened awareness of structure, while the updated vocal features provide more lifelike expression, emotional depth, and clearer articulation. Users can start with a basic concept or elaborate on their vision by specifying details such as genre, instrumentation, mood, key, tempo, vocal style, language, and production characteristics, allowing for a tailored sound experience. Lyria 3.5 accommodates varying song lengths, enabling creators to request anything from a brief 60-second snippet to a full-length track, up to three minutes in duration. Moreover, it can generate music across diverse genres and languages, encompassing styles ranging from pop, funk, and R&B to reggaeton and jazz fusion, making it a versatile tool for musicians worldwide. This flexibility empowers artists to explore and innovate within their musical endeavors.
Description
We are excited to unveil Jukebox, a cutting-edge neural network designed to create music, including basic vocalization, in diverse genres and artistic expressions as raw audio. Alongside the release of the model weights and code, we are offering a tool to help users explore the music samples generated by Jukebox. By inputting genre, artist, and lyrics, users can receive entirely new music pieces crafted from the ground up. Jukebox is capable of producing a vast array of musical and vocal styles, and it can also generalize to lyrics that were not part of the training dataset. The lyrics included here have been collaboratively crafted by researchers at OpenAI and a language model. When provided with lyrics from its training set, Jukebox generates songs that diverge significantly from the originals, showcasing its creative capabilities. Users can input a 12-second audio clip for Jukebox to build upon, with the final output reflecting a desired style. Our focus on music stems from a desire to advance the potential of generative models further. Utilizing a quantization-based approach called VQ-VAE, Jukebox’s autoencoder model effectively compresses audio into a discrete latent space, enabling innovative sound generation. As we continue to refine these technologies, we look forward to the creative possibilities that lie ahead.
API Access
Has API
API Access
Has API
Integrations
Gemini
Gemini Enterprise Agent Platform
Google AI Studio
Google Cloud Platform
Google Flow Music
Google Vids
Lyria
Microsoft Azure
Music AI Sandbox
OpenAI
Integrations
Gemini
Gemini Enterprise Agent Platform
Google AI Studio
Google Cloud Platform
Google Flow Music
Google Vids
Lyria
Microsoft Azure
Music AI Sandbox
OpenAI
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
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
Founded
1998
Country
United States
Website
blog.google/innovation-and-ai/models-and-research/google-labs/lyria-3-5/
Vendor Details
Company Name
OpenAI
Founded
2015
Country
United States
Website
openai.com/blog/jukebox/