AI assisted music ideation and generation
Our team aims to develop an application that enables users to create compositions and musical motifs with the help of certain music-generation models that take their voice as input in real time to transcribe the melody into different instruments. Users can also generate beats according to certain rhythmic measures and use them as backing to combine these tracks into a final piece. In this way, any user can realise the melodic ideas they have in mind. Moreover, by transcribing the instruments, users do not have to pay the extra cost of the instrumenst and midi keyboards.
AudioGeeks – MuGEN
AI assisted music ideation and generation
Our team aims to develop an application that enables users to create compositions and musical motifs with the help of certain music-generation models that take their voice as input in real time to transcribe the melody into different instruments. Users can also generate beats according to certain rhythmic measures and use them as backing to combine these tracks into a final piece. In this way, any user can realise the melodic ideas they have in mind. Moreover, by transcribing the instruments, users do not have to pay the extra cost of the instrumenst and midi keyboards.
Team member(s)
Mr Jrenoth Misquith* (Undergraduate student, Dept. of Computer Science, CityU)
Mr Yussif Bamie Mubashir (Undergraduate student, Dept. of Electrical Engineering, CityU)
* Person-in-charge
(Info based on the team's application form)
Achievement(s)
- CityU HK Tech 300 Seed Fund (2024)