DocumentCode :
3693990
Title :
Electric bass guitar e-learning system
Author :
Toky Hajatiana Raboanary;Fanaja Harianja Randriamahenintsoa;Heriniaina Andry Raboanary;Julien Amédée Raboanary;Tantely Mahefatiana Raboanary
Author_Institution :
Department of Computer Science, Institut Supé
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, we describe a system that we have designed and implemented for learning to play electric bass guitar. This system is called EBGeL System or Electric Bass Guitar e-Learning System. EBGeL System includes advanced features for training and practices, and gives feedbacks to users by assessing their performance. It provides models that the electric bass guitar player should follow. Models are represented by musical metadata which have musical components. We describe the steps handled by the EBGeL System for the audio signal processing in order to assess the input audio played by the user: transcription into musical score, extraction of plucking and expression styles, and musical metadata comparison. In particular, the EBGeL System gives marks and reports to users according to their ability with respect to musical rules and playing techniques related to electric bass guitar. That helps the electric bass guitar player to upgrade his level. Experiments indicate that EBGeL System can challenge any methods for learning to play electric bass guitar: users found it easy to use, they appreciated the quickness of the learning process in contrast to the other means of learning to play electric bass guitar.
Keywords :
"Metadata","Training","Thumb","Electronic learning","Software","Signal processing"
Publisher :
ieee
Conference_Titel :
AFRICON, 2015
Electronic_ISBN :
2153-0033
Type :
conf
DOI :
10.1109/AFRCON.2015.7331992
Filename :
7331992
Link To Document :
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