Shades of Music: Letting Users Discover Sub-Song Similarities
نویسندگان
چکیده
Many interesting pieces of music violate established structures or rules of their genre on purpose. These songs can be very atypical in their interior structure and their different parts might actually allude to entirely different other songs or genres. We present a query-by-example-based user interface that shows songs related to the one currently playing. This relation is not based on overall similarity, but on the similarity between the part currently playing and parts of other songs in the collection along different dimensions (pitch, timbre, bars, beats, loudness). The similarity is initially computed automatically, but can be corrected by the user. Once a sufficient number of corrections has been made, we expect the similarity measure to reach an even higher precision. Our system thereby allows users to discover hidden similarities on the level of song sections instead of whole songs.
منابع مشابه
Analaysis of IFLA Library Refrence Model’s Entities and Attrbutes For Iranian Traditional Music Resources (Case study: Morq-e sahar Song)
Background and Aim: The object of the study was to Analyze IFLA Library Reference Model (LRM) Entities and Attributes for Iranian Traditional Music Resources, Case Study: Morq-e Sahar Song. Method: The study inherits an applied content analysis method. All Entities and Attributes of IFlA LRM Model based on two checklists include: Final report of IFlA LRM on August 2017 and Transition Mappi...
متن کاملStrike-A-Tune: Fuzzy Music Navigation Using a Drum Interface
Project Goals • "Fuzzy" Navigation • Physically and Visually Intuitive • Large Libraries A traditional music library system controlled by a mouse and keyboard is precise, allowing users to select their desired song. Alternatively, randomized playlist or shuffles are used when users have no particular music in mind. We present a new interface and visualization system called Strike-A-Tune for fuz...
متن کاملDiscovering Shades of Attribute Meaning with the Crowd
To learn semantic attributes, existing methods typically train one discriminative model for each word in a vocabulary of nameable properties. This “one model per word” assumption is problematic: while a word might have a precise linguistic definition, it need not have a precise visual definition. We propose to discover shades of attribute meaning. Given an attribute name, we use crowdsourced im...
متن کاملAudio Fingerprinting " A New Technology To Identify Music "
This report describes the core of the audio fingerprinting technology that was developed at Philips Research. An audio fingerprint is a unique code that uniquely identifies a segment of music like a human fingerprint identifies a human being. Audio fingerprinting can be used for several applications: • Broadcast monitoring to automatically generate playlists of radio stations • Connected audio:...
متن کاملMusic Genie: Interactive, Content-Based Browsing of Music Based on Thumbnail Playback
Music Genie refers to audio processing technologies for quick and easy music browsing and discovery. We built research prototype software that allows users to quickly generate playlists from a collection of thousands of songs. Our software provides an interactive, content-adaptive, thumbnail-based presentation of music. The software accepts user inputs interactively during use, and it consecuti...
متن کامل