Citation :

Seema Chaudhary, Dr Sangeeta Kakarwal, 2023. "Indian Musical Instrument Recognition Using Integrated Mean Method" ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 1, Issue 1: 5-10.

Abstract :

Daily, numerous musical works are uploaded on social media platforms. The process of searching for content according to our preferences is time-consuming. One of the emerging research fields that is concerned with the process of extracting content from audio data is known as musical information retrieval. The field of musical information retrieval contains a subfield known as musical instrument recognition. Previous studies had primarily concentrated on a variety of western instruments that belonged to diverse families, such as brass, string, and woodwind instruments. The objective of this research is to categorize different types of musical instruments by making use of the Integrated Mean technique and acoustic features. The experiments make use of homophonic recordings of musicians performing solo on their instruments. Temporal and spectral aspects of sound have been accounted for in acoustic features. The new approach Integrated Mean method provides a vector that combines the mean that was obtained with the features that were extracted. A produced vector is used to categorize the musical instruments of the IRMAS and ISI-500 dataset. The proposed method obtained higher accuracy than using audio features independently. The K-nearest neighbour classifier has been utilized here for the purpose of classification.

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Keywords :

Social Media, Sentiment Analysis (SA),Text-based Classification, Polyglot.