Research Article Open Access

A Survey on Audio Retrieval System for Classification

Abstract

In today’s environment, most of the retrieval algorithms are textual based algorithm therefore we cannot able to make classification of musical instruments. In most of the retrieval system the classification can be done on the basis of term frequencies and use of snippets in any documents. Existing search engines (like Yahoo, Google, AltaVista etc.) make similarity search on the basis of Key-word and snippets, but sometimes user may not able to express the queries in words so we have to switch to audio retrieval system. In existing audio visual retrieval system,Content-Based retrieval systems user can enter any queries ranging from drawing sketch to sing a song or a video clip or set of images from some video short for a video retrieval. Which add more comprehensive approach for users to enter their queries .From [11]we can say that content-based retrieval system permits more tolerance towards erroneous queries, as in these systems queries contain more errors; so for such search keys similarity search based on approximate matching produce batter results compare to exact matching. In existingsystem, systems are classified based on audio object representation, indexing structure and retrieval technique used. In our proposed system we are extracting the sound by recognizing the timbre of sound. In many existing audio retrieval system we extract the features either by linear predictive code or by perceptual linear prediction. But in proposed system for extraction we use musical information retrieval toolbox (MIR toolbox) which is useful to find out audio descriptor by using hybrid selection method. After finding audio descriptor we identify the musical instruments with the help of vector quantization

Priyanka S. Jadhav., Saurabh H. Deshmukh

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