  Learning musical instruments using online instructional videos has become
increasingly prevalent. However, pre-recorded videos lack the instantaneous
feedback and personal tailoring that human tutors provide. In addition,
existing video navigations are not optimized for instrument learning, making
the learning experience encumbered. Guided by our formative interviews with
guitar players and prior literature, we designed Soloist, a mixed-initiative
learning framework that automatically generates customizable curriculums from
off-the-shelf guitar video lessons. Soloist takes raw videos as input and
leverages deep-learning based audio processing to extract musical information.
This back-end processing is used to provide an interactive visualization to
support effective video navigation and real-time feedback on the user's
performance, creating a guided learning experience. We demonstrate the
capabilities and specific use-cases of Soloist within the domain of learning
electric guitar solos using instructional YouTube videos. A remote user study,
conducted to gather feedback from guitar players, shows encouraging results as
the users unanimously preferred learning with Soloist over unconverted
instructional videos.
