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Use of Tonic and Raga as Indices for a Query by Example based Music Information Retrieval System
Background and Objectives: A Music Information Retrieval Systems deal with retrieving music from a corpus based on user’s input. Query by Example (QBE) and Query By Humming (QBH) are the two content baste music information retrieval systems. Methods/Statistical Analysis: In this paper, a Query By Example (QBE) based Music Information Retrieval system is proposed, where the characteristics of Carnatic music are used as indices for identifying similar matches to an input song. The system begins by introducing a novel focused crawler mechanism that explores the World Wide Web in a methodical manner to harvest music for the database required. The crawled music is then downloaded, and a local repository of songs is created. Carnatic music features like Tonic and Raga are extracted from the crawled songs and these songs are indexed into the database. Tonic identification is a challenging problem and in this work, a new algorithm for estimation of tonic is designed. Using the Tonic, the Raga of the song is identified and these features are used in a modified, optimized version of the Multi-key hashing technique to index the songs and improve the speed of retrieval. During a user query, which is by example, the same features are extracted, compared with the features of the songs indexed in the database, based on the search option provided by the user, and the best matching songs are retrieved, by proposing a new ranking algorithm based on Raga and Tonic similarity. Findings: The proposed system recognized the Tonic of the song with accuracy while the Raga of the song is recognized if the input music piece is free of Gamaka. Application/ Improvements: Music information retrieval system for entertainment, therapy and helps in content based retrieval of music and the system could be improved to handle Gamakas in the input music piece.
Focused Crawler, Music Information Retrieval, Multi-Key Hashing, Query By Example, Raga, Tonic.
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