NDLI: An Effective Feature Calculation For Analysis & Classification of Indian Musical Instruments Using Timbre Measurement

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An Effective Feature Calculation For Analysis & Classification of Indian Musical Instruments Using Timbre Measurement

Content Provider	ACM Digital Library
Author	Shelke, Akshata Chitre, Abhijit
Abstract	Musical instrument recognition is significant field in the research of computer music which is related to the modelling of sounds. Analysing & synthesing the structure of musical note is of importance both for modelling music signals and their automatic computer-based recognition. Musical sound is produce by five dimensions: pitch, loudness, duration, spatialization, and timbre. First four parameter can be controlled but timbre remains difficult. Timbre then naturally became the main subject of this work. It is important property of sound that separate one music instrument from another and independent of pitch and volume. This work presents a system for identifying a specific musical instrument from monophonic recordings. The system proposed in this paper has been trained and tested with three Indian musical instruments samples. Instruments include flute, harmonium and sitar, which are most commonly used in Indian classical music. The Statistical and spectral parameter are used for the classification of the sounds in Indian Musical Instruments. The SVM classifier proves its ability in automatic and accurate classification of Indian Musical Instrument. Using separately recorded notes as test sets, we were able to achieve average accuracy as high as 88.88 % for SVM that deciding if a note is played by the sitar or others.
Starting Page	101
Ending Page	105
Page Count	5
File Format	PDF
ISBN	9781450335522
DOI	10.1145/2818567.2818586
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-09-25
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Support vector machine (svm) Musical instrument identification Timbre time-domain Timbre Timbre spectral domain Musical signal processing
Content Type	Text
Resource Type	Article

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