Polymath
Polymath is a versatile AI tool that uses machine learning to convert any music library into a music production sample-library. It automatically separates songs into stems, quantizes them to the same tempo and beat-grid, analyzes musical structure and key, and converts audio to MIDI. Polymath streamlines the workflow for music producers, DJs, and ML developers, making it easy to create unique compositions, polished DJ sets, and large music datasets.
Features of Polymath
- Music Source Separation: Polymath uses the Demucs neural network to perform music source separation. This allows the tool to separate songs into different stems such as beats, bass, etc.
- Music Structure Segmentation/Labeling: The tool uses the sf_segmenter neural network to perform music structure segmentation and labeling. This helps in analyzing the musical structure of songs, such as verse, chorus, etc.
- Music Pitch Tracking and Key Detection: Polymath uses the Crepe neural network for music pitch tracking and key detection. This helps in identifying the key of songs, such as C4, E3, etc.
- Music to MIDI Transcription: The tool uses the Basic Pitch neural network to convert music to MIDI. This feature is particularly useful for music producers and DJs.
- Music Quantization and Alignment: Polymath uses pyrubberband for music quantization and alignment. This helps in aligning the songs to the same tempo and beat-grid.
- Music Info Retrieval and Processing: The tool uses librosa for music info retrieval and processing. This helps in analyzing various aspects of songs such as timbre, loudness, etc.
Benefits of Polymath
- Streamlined Workflow for Music Producers and DJs: Polymath streamlines the workflow for music producers and DJs by converting any music library into a music production sample-library. The tool automatically separates songs into stems, quantizes them to the same tempo and beat-grid, analyzes musical structure, key, and other info, and converts audio to MIDI.
- Creation of Unique Compositions: Polymath makes it effortless to combine elements from different songs to create unique new compositions. Users can simply grab a beat from one track, a bassline from another, and fitting horns from a third song, and seamlessly integrate them into their DAW in record time.
- Simplified Process of Creating a Large Music Dataset: For ML developers, Polymath simplifies the process of creating a large music dataset, which can be used for training generative models, etc.
Who Polymath is useful for
- Music Producers: Polymath is a great tool for music producers as it streamlines the process of creating new compositions by combining elements from different songs.
- DJs: DJs can benefit from Polymath as it allows them to create a polished, hour-long mash-up DJ set with ease.
- ML Developers: ML developers who are working on projects related to music can use Polymath to simplify the process of creating a large music dataset.
In conclusion, Polymath is a versatile AI tool that offers a wide range of features for music producers, DJs, and ML developers. By leveraging machine learning, it streamlines the process of music production and simplifies the creation of large music datasets. Whether you're a music producer looking to create unique compositions, a DJ wanting to create a polished set, or an ML developer needing a large music dataset, Polymath is a tool worth considering.