MusicLM
MusicLM
MusicLM
AI & Machine Learning Development
AI Music
Open Source
Text-to-music
Melody conditioning
Long-duration generation
High fidelity audio
AI & Machine Learning Development
AI Music
Open Source
Text-to-music
Melody conditioning
Long-duration generation
High fidelity audio
AI & Machine Learning Development
AI Music
Open Source
Text-to-music
Melody conditioning
Long-duration generation
High fidelity audio
Key Features
High-fidelity music generation, Hierarchical sequence-to-sequence modeling, Text and melody conditioning, Consistent long-duration music, Open-source dataset MusicCaps.
Key Features
High-fidelity music generation, Hierarchical sequence-to-sequence modeling, Text and melody conditioning, Consistent long-duration music, Open-source dataset MusicCaps.
Key Features
High-fidelity music generation, Hierarchical sequence-to-sequence modeling, Text and melody conditioning, Consistent long-duration music, Open-source dataset MusicCaps.
Pricing Details
Open Source
As an open-source tool, MusicLM is available for free, encouraging researchers, developers, and musicians to explore and contribute to the technology.
Open Source
As an open-source tool, MusicLM is available for free, encouraging researchers, developers, and musicians to explore and contribute to the technology.
In a Nutshell
USEFUL FOR
AI Enthusiasts, Researchers, and Developers
POTENTIAL INTEGRATIONS
Integration with music production software, Educational tools for music theory and composition, AI-driven content creation platforms, Music recommendation systems.
USEFUL FOR
AI Enthusiasts, Researchers, and Developers
POTENTIAL INTEGRATIONS
Integration with music production software, Educational tools for music theory and composition, AI-driven content creation platforms, Music recommendation systems.
USEFUL FOR
AI Enthusiasts, Researchers, and Developers
POTENTIAL INTEGRATIONS
Integration with music production software, Educational tools for music theory and composition, AI-driven content creation platforms, Music recommendation systems.
MusicLM by Google Research introduces a hierarchical sequence-to-sequence model capable of generating high-fidelity music at 24 kHz from text descriptions. The model excels in both audio quality and adherence to given text descriptions, and uniquely, it can also condition music generation on both text and melodies. MusicLM supports the generation of music that remains consistent over several minutes, showcasing prowess in creating audio that reflects complex descriptions like mood, instrumental composition, and genre. Furthermore, to bolster future research and innovation in the field, the MusicCaps dataset with 5.5k music-text pairs is released, enriching the ecosystem for AI-driven music composition.
MusicLM by Google Research introduces a hierarchical sequence-to-sequence model capable of generating high-fidelity music at 24 kHz from text descriptions. The model excels in both audio quality and adherence to given text descriptions, and uniquely, it can also condition music generation on both text and melodies. MusicLM supports the generation of music that remains consistent over several minutes, showcasing prowess in creating audio that reflects complex descriptions like mood, instrumental composition, and genre. Furthermore, to bolster future research and innovation in the field, the MusicCaps dataset with 5.5k music-text pairs is released, enriching the ecosystem for AI-driven music composition.
MusicLM by Google Research introduces a hierarchical sequence-to-sequence model capable of generating high-fidelity music at 24 kHz from text descriptions. The model excels in both audio quality and adherence to given text descriptions, and uniquely, it can also condition music generation on both text and melodies. MusicLM supports the generation of music that remains consistent over several minutes, showcasing prowess in creating audio that reflects complex descriptions like mood, instrumental composition, and genre. Furthermore, to bolster future research and innovation in the field, the MusicCaps dataset with 5.5k music-text pairs is released, enriching the ecosystem for AI-driven music composition.