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Večmodalni priporočilni sistem za glasbo
Jakša, Silvester (Author), Divjak, Saša (Mentor) More about this mentor... This link opens in a new window

URLURL - Presentation file, Visit http://eprints.fri.uni-lj.si/3049/ This link opens in a new window

Abstract
V diplomskem delu je obravnavan razvoj večmodalnega sistema za priporočanje glasbe. Uporabniki sistema se z mobilno aplikacijo sprehajajo po mostu in sistem glede na način hoje priporoča glasbo, prilagaja tempo predvajane pesmi, osvetljuje most in projicira pozicijo uporabnikov na tla. V ta namen smo razvili elektronska vezja za naprave, ki spremljajo premike uporabnikov in jih povezali v enotno strojno opremo, ki komunicira z računalnikom Raspberry Pi. Z mobilno aplikacijo zaznavamo tempo hoje uporabnikov, ki ga skupaj s podatki strojne opreme pošiljamo multimedijskemu strežniku. Multimedijski strežnik glede na pridobljene podatke iz lokalnega omrežja predvaja glasbo in generira projekcijo. Predvajanje glasbe in osvetljevanje mostu se generira avtomatsko in se priporoča uporabnikom v povezavi s podatkovno bazo Moodo. Dodatna funkcija sistema je igranje klavirske glasbe glede na pozicijo uporabnikov v prostoru. Evalvacijo sistema smo opravili na mestu testiranja s kratkim vprašalnikom. Rezultati so pokazali, da sistem uporabnikom predstavlja popestritev vsakdana.

Language:Unknown
Keywords:priporočanje glasbe, večmodalna percepcija, senzorji razdalje, Raspberry Pi, Moodo podatkovna baza, mobilna aplikacija, MoodWalker
Work type:Not categorized (r6)
Organization:FRI - Faculty of computer and information science
Year:2015
COBISS.SI-ID:1536474819 Link is opened in a new window
Views:491
Downloads:121
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Secondary language

Language:Unknown
Title:Multimodal System for Recommending Music
Abstract:
Our work discusses development of multimodal music recommendation system. Users of the system are walking on the bridge while using mobile application and the system recommends music according to the walking style, adjusts tempo of the playing song, illuminates the bridge and projects user's positions on the floor. For this particular project we developed electronic boards and used them for all user tracking devices. All electronic boards are merged into common hardware which communicates with Rasberry Pi computer. Walking tempo is detected by mobile application which sends all acquired data to multimedia server together with the hardware data. Multimedia server receives data from local network and projects user's positions and generates music. Music and bridge illumination is generated automatically and is recommended to users according to Moodo dataset. Additional system function is playing piano tones which plays regarding users presence on the bridge and their position. The system evalvation was done using short survey after every use. The results showed that the system presents diversification in users daily routine.

Keywords:music recommendation, multimodal perception, proximity sensors, Raspberry Pi, Moodo dataset, mobile application, Moodwalker

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