Hang the DJ: Automatic Sequencing and Seamless Mixing of Dance-Music Tracks
نویسنده
چکیده
Many radio stations and night-clubs employ Disk-Jockeys (DJs) to provide a continuous stream or “mix” of music, built from a sequence of individual song-tracks. In the last decade, commercial pre-recorded compilation CDs of DJ mixes have become a booming market. DJs exercise skill in deciding an appropriate sequence of tracks and in mixing 'seamlessly' from one track to the next. Online access to large-scale archives of digitized music via automated music information retrieval systems offers users the possibility of discovering many new songs they like, but the majority of consumers are unlikely to want to learn the DJ skills of sequencing and mixing. This paper describes an automatic method by which compilations of dance-music can be sequenced and seamlessly mixed by computer, with minimal user involvement. The user may specify a selection of tracks, and may give a qualitative indication of the type of mix required. The resultant mix can be presented as a continuous single digital audio file, whether for burning to CD or for play-out from a virtual jukebox or personalized virtual radio station. Topic Area: User interfaces for music information retrieval.
منابع مشابه
Automating Music Production with Music Information Retrieval
Prior research in the field of Music Information Retrieval has yielded techniques for extracting musical information from digital audio, and made it possible to analyze human music production computationally. I hypothesize that a computer can be programmed to produce output similar to that of a musical artist on two production tasks performed by disk jockeys. The first, " mixing, " aims to crea...
متن کاملAutomatic Playlist Sequencing and Transitions
Professional music curators and DJs artfully arrange and mix recordings together to create engaging, seamless, and cohesive listening experiences, a craft enjoyed by audiences around the world. The average listener, however, lacks both the time and the skill necessary to create comparable experiences, despite access to same source material. As a result, user-generated listening sessions often l...
متن کاملA Long-Range Self-similarity Approach to Segmenting DJ Mixed Music Streams
In this paper we describe an unsupervised, deterministic algorithm for segmenting DJ-mixed Electronic Dance Music (EDM) streams (for example; podcasts, radio shows, live events) into their respective tracks. We attempt to reconstruct boundaries as close as possible to what a human domain expert would engender. The goal of DJ-mixing is to render track boundaries effectively invisible from the st...
متن کاملEnchantment under the sea: An intelligent enviroment
Disc Jokeys (DJs) generally mix music in a confined isolated space. This can make the DJ have depression sentiments and it can also difficult the DJ's understanding of his public. We present Enchantment Under The Sea: a new intelligent environment that allows the disc jokey to roam freely, interact directly with his audience, receive informative feedback about the public's social interactions, ...
متن کاملEmpirical Analysis of Track Selection and Ordering in Electronic Dance Music using Audio Feature Extraction
Disc jockeys are in some ways the ultimate experts at selecting and playing recorded music for an audience, especially in the context of dance music. In this work, we empirically investigate factors affecting track selection and ordering using mixes created for the Essential Mix. The Essential Mix is a well known weekly radio show on BBC Radio 1 that showcases various styles of electronic dance...
متن کامل