A groundbreaking new company, Songscription, recently emerged onto the music scene, introducing cutting-edge AI technology that revolutionizes music transcription. This innovative platform transforms audio files of songs into sheet music with remarkable speed and accuracy, catering to both seasoned professionals and enthusiastic hobbyists.
“Our mission at Songscription is to enhance the joy of playing music,” remarked Andrew Carlins, the CEO of this trailblazing startup and a student enrolled in Stanford’s MBA/MA in Education program. He envisions a future where even a small-town high school band teacher in rural Nebraska can access customized sheet music for their students, tailored to each individual’s skill level and instrument.
Upon its launch, Songscription boasts the ability to transcribe music for various instruments, with its piano model standing out for its reliability. The company aims to expand its offerings in the future, introducing different transcription outputs like guitar tabs and full band arrangements.
This groundbreaking product streamlines the music-making process for artists who record their compositions, enabling them to effortlessly obtain accurate sheet music without the hassle of manual transcription. Additionally, Songscription provides a piano roll feature for those who are not proficient in reading traditional sheet music, offering a visual representation of the music on a digital piano.
Users can even transcribe music directly from YouTube links, simplifying the process further. While ensuring users have the rights to transcribe copyrighted material, Songscription acknowledges the evolving legal landscape surrounding AI tools in the creative industry.
Songscription emphasizes that its platform is designed to assist musicians in expediting the transcription process, positioning itself as an augmented music notation software rather than a creator of AI-generated music.
The AI model underpinning Songscription’s technology is rooted in a research paper authored by co-founder Tim Beyer and researcher Angela Dai. To train this model effectively, Songscription collaborates with musicians who share or sell their performances and sheet music, supplementing the data with synthetic content for comprehensive training.
In a testament to its rapid growth and potential, Songscription has secured pre-seed funding from Reach Capital within a mere seven months of its inception and is set to partake in Stanford’s esteemed StartX accelerator program.
