Signal Processing and Machine Learning Approaches and Evaluation for Indian Classical Music

EasyChair Preprint 4916

Abstract

In the field of signal processing, a large amount of work has been done in the analysis and implementation of various techniques related to speech signal processing. When it comes to the Music signal processing, the techniques which are originally developed for speech signal processing have been applied to music signal with good results. As per the present literature, there has been a lot of work done on music audio analysis in terms of information retrieval, genre detection, and instrument/singer identification of western classical music, in comparison with Indian classical music. This paper provides an overview of some signal processing, and machine learning techniques that specifically applied to the Indian classical music for analyzing and identifying features such as tonic identification, genre classification, raga recognition, music transcription, rhythm, and timbre. We will look at how particular features of Indian Classical music signals impact and how these features are extracted.

Keyphrases: Indian Classical Music, Raga, machine learning, signal processing

@booklet{EasyChair:4916,
  author    = {Rajashekhar Shastry and Anita Bai},
  title     = {Signal Processing and Machine Learning Approaches and Evaluation for Indian Classical Music},
  howpublished = {EasyChair Preprint 4916},
  year      = {EasyChair, 2021}}