The field of music generation and interaction is rapidly evolving, with a focus on developing innovative systems that can create high-quality music pieces and provide intuitive user interfaces. Recent advancements have led to the development of multimodal music generation models that can generate music from diverse conditional information, such as images, story texts, and music captions. These models have the potential to make music creation more accessible to ordinary users, regardless of their musical expertise.

Noteworthy papers in this area include MusFlow, which introduces a novel multimodal music generation model using Conditional Flow Matching, and Mozualization, which presents a music generation and editing tool that creates multi-style embedded music by integrating diverse inputs.

Another area of research is the development of brain-computer interfaces (BCIs) for music interaction, such as Auditory Conversational BAI, which enables users to select among multiple auditory options by analyzing their brain responses.

Additionally, researchers are exploring the use of cross-sensory metaphors to support creative thinking and embodied practice in music interaction, as seen in Mixer Metaphors, which uses interface metaphors borrowed from analogue synthesisers and audio mixing to physically control the intangible aspects of a Large Language Model.

The development of interactive music applications, such as Apollo and Calliope, is also a significant trend in this field. These applications enable users to generate symbolic musical phrases and multi-track compositions using corpus-based style imitation techniques and machine learning approaches.

Overall, the field of music generation and interaction is advancing rapidly, with a focus on developing innovative systems that can create high-quality music pieces and provide intuitive user interfaces. These advancements have the potential to make music creation more accessible to a wider range of users and to revolutionize the way we interact with music.