We verified the applicability and effectiveness of the proposed system in a drum-playing game with adult human test subjects by evaluating it both objectively and subjectively. As a part of those scenarios, a system that enables drum strokes to be automatically detected and recognized using auditory cues was implemented and incorporated into the experimental framework. Three interactive scenarios with different experimental setups for humanoid robots and mobile devices were developed and tested. For that purpose, we created an interactive drumming game relying on turn-taking and imitation principles, in which a human user is able to play drums with a humanoid robot (Robotic Drum Mate). Several parameters, including the effect of the embodiment of the tutor/interface and the presence of feedback and training mechanisms, were the focus of interest. It specifically focuses on evaluating robot/virtual avatar tutors, tangible interaction devices, and mobile multimedia devices within a simple drumming-based interactive music tutoring game scenario. This study is part of a project to design robot and avatar assistants for education and therapy, especially for children with special needs. The interactive multimodal drumming game is used in conjunction with humanoid robots to establish an audiovisual interactive interface. This paper presents a study of an audiovisual interface-based drumming system for multimodal human–robot interaction. We anticipate that the community will find yet more uses for the data, in applications from automatic loop characterisation to algorithmic composition. To illustrate the usefulness of FSLD, we present short case studies on using it to estimate tempo and key, generate music tracks, and evaluate a loop separation algorithm. We also present to the community an online loop annotator tool that we developed. We describe the methodology used to assemble and annotate the data, and report on the distribution of tags in the data and inter-annotator agreement. The annotations include instrument, tempo, meter, key and genre tags. The loops originate from Freesound, a community database of audio recordings released under Creative Commons licenses, so the audio in our dataset may be redistributed. We present the Freesound Loop Dataset (FSLD), a new large-scale dataset of music loops annotated by experts.

Several commercial and community databases have been created to meet this demand, but most are not suitable for research due to their strict licensing.

Music loops are essential ingredients in electronic music production, and there is a high demand for pre-recorded loops in a variety of styles.

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