SnapJam App

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Publisher: R&R Innovation
Client: tunehog
Product: Combines Photos and Music
Format: iOS
SourceiTunes App Store
Site: snapjam.tunehog.com

SnapJam uses colour identification technology to match music to images. Songs are classified under ‘colour-mood’ categories and then applied to the image colour analysis reading. Users can then share their SnapJam music supported images across social media.

snapjam

Zodiac Music App

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Publisher: R&R Innovation
Client: TBA
Product: Astrology based music player
Format: iOS, Android
Source: TBA

The zodiac music app generates playlists and music recommendations based on profile data inputted by the user and astrological readings sent by partner astrology services. Using patented algorithms, the music player is able to deliver targeted content to the user based on their mood, star sign and other profile and astrological information. The app offers daily playlists and astrology readings as well as more personalised Natal Chart readings and music recommendations.

 

 

 

 

 

Music Discovery Player

Radio presentation

Publisher: R&R Innovation
Client: tunehog
Product: Music Discovery App
Format: Android
Source: Google Play Store
Site: androidtunehog.com

tunehog Discovery app (V.1)  uses unique sonic processing algorithms to auto-generate playlists based on the users seed song. This means songs are recommended to the user based on their musical qualities, rather than collaborative or meta data filtering methods used by most other music tools.

The app allows users to explore their music taste both actively and passively with a recommendation tool, Radio player and the option to play music videos via Youtube.

Future iterations of this app will look to improve the level of content personalisation for the user, with increased data sourcing as well as targeted and curated content.

 

 

Radio App

tunehog Radio app

Publisher: R&R Innovation
Client: tunehog
Product: Radio App
Format: iOS
Source: iTunes App Store

tunehog Radio app (V.1)  uses unique sonic processing algorithms to auto-generate playlists based on the users seed song. This means songs are recommended to the user based on their musical qualities, rather than collaborative or meta data filtering methods used by most other music tools.

The designer of the player interface for this app has won awards for his UI design.

Future iterations of this app will look to improve the level of content personalisation for the user, with increased data sourcing as well as targeted and curated content.