Intelligent User Interfaces for Music Discovery

Abstract

Assisting the user in finding music is one of the original motivations that led to the establishment of Music Information Retrieval (MIR) as a research field. This encompasses classic Information Retrieval inspired access to music repositories that aims at meeting an information need of an expert user. Beyond this, however, music as a cultural art form is also connected to an entertainment need of potential listeners, requiring more intuitive and engaging means for music discovery. A central aspect in this process is the user interface. In this article, we reflect on the evolution of MIR-driven intelligent user interfaces for music browsing and discovery over the past two decades. We argue that three major developments have transformed and shaped user interfaces during this period, each connected to a phase of new listening practices. Phase 1 has seen the development of content-based music retrieval interfaces built upon audio processing and content description algorithms facilitating the automatic organization of repositories and finding music according to sound qualities. These interfaces are primarily connected to personal music collections or (still) small commercial catalogs. Phase 2 comprises interfaces incorporating collaborative and automatic semantic description of music, exploiting knowledge captured in user-generated metadata. These interfaces are connected to collective web platforms. Phase 3 is dominated by recommender systems built upon the collection of online music interaction traces on a large scale. These interfaces are connected to streaming services. We review and contextualize work from all three phases and extrapolate current developments to outline possible scenarios of music recommendation and listening interfaces of the future.

Explainability in Music Recommender Systems

“…Various use cases of MRSs exist, centered around different tasks. Among these, the most important ones are front page recommendation (recommending content for thematic collections of music -also known as shelves or channelspresented to the user on the front page of the platform's user interface) [11], music exploration/discovery (e. g., based on item similarity in terms of melody, rhythm, or lyrics) [41,60], automatic playlist generation (commonly based on the user profile, but possibly only based on a seed description such as "music to relax"), and automatic playlist continuation (based on a sequence of seed tracks) [50,117].…”

EmoMTB: Emotion-aware Music Tower Blocks

“…For a comprehensive survey of intelligent user interfaces for music discovery, please refer to Knees et al [7]. Most related music user interfaces create a spatial arrangement of musical collections.…”

Generating Interesting Song-to-Song Segues With Dave

“…The study of intelligent user interfaces for music retrieval has been an active research topic for twenty years now [17]. The main goal of early interfaces was to facilitate the browsing of personal music collections, for example, by representing songs in 2D or 3D maps.…”

“…Recently, with the advent of streaming services, the quantity of music available to listeners shifted from relatively small personal collections to, virtually, all music content. Modern interfaces are, for the most part, not built to handle the visualization of these very large collections, but to automatically search for personalized sets of songs, and to show just these to the user [17]. In Pampalk et al [29], for example, new artists are recommended based on a seed artist picked by the user.…”