2026-09-19T18:47:47Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1572492024-10-10T03:36:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Egozy, Eran
Jaco, Wasalu
Arora, Ajay
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2024-10-09T18:31:09Z
2024-10-09T18:31:09Z
2024-09
2024-10-07T14:34:28.000Z
https://hdl.handle.net/1721.1/157249
We propose SongGen, an AI-based song-writing and song co-creation framework. Building upon existing AI tools like Suno.ai, SongGen features a chat interface with a trained AI songwriter assistant, emulating the traditional back-and-forth of human collaboration. The system offers enhanced capabilities for greater control over the songwriting process, including concept ideation, lyric generation and editing, real-time song generation, and granular instrumental specification. Comparative evaluations demonstrate SongGen’s superiority in key metrics such as steerability, expressiveness, personalization, and user satisfaction. We also present an extension of the SongGen framework for artist emulation and on-demand song generation. Future development aims to incorporate voice-based interaction and real-time voice conversion, enabling music artists to guide fans in creating personalized songs.
M.Eng.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright retained by author(s)
https://rightsstatements.org/page/InC-EDU/1.0/
SongGen: Framework for Controllable AI Song Generation through Interactive Songwriting and Artist Emulation
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="84be86d4-109f-4831-82a8-f26136a033b5">
<Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type>
<Title>SongGen: Framework for Controllable AI Song Generation through Interactive Songwriting and Artist Emulation</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>2024-09</PublicationDate>
<Authors>
<Author>
<DisplayName>Arora, Ajay</DisplayName>
<Affiliation>
<OrgUnit>
</OrgUnit>
</Affiliation>
</Author>
</Authors>
<Editors>
</Editors>
<Publishers>
<Publisher>
<DisplayName>Massachusetts Institute of Technology</DisplayName>
<OrgUnit />
</Publisher>
</Publishers>
<License>https://rightsstatements.org/page/InC-EDU/1.0/</License>
<Abstract>We propose SongGen, an AI-based song-writing and song co-creation framework. Building upon existing AI tools like Suno.ai, SongGen features a chat interface with a trained AI songwriter assistant, emulating the traditional back-and-forth of human collaboration. The system offers enhanced capabilities for greater control over the songwriting process, including concept ideation, lyric generation and editing, real-time song generation, and granular instrumental specification. Comparative evaluations demonstrate SongGen’s superiority in key metrics such as steerability, expressiveness, personalization, and user satisfaction. We also present an extension of the SongGen framework for artist emulation and on-demand song generation. Future development aims to incorporate voice-based interaction and real-time voice conversion, enabling music artists to guide fans in creating personalized songs.</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>