Publications (1)4.63 Total impact

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    B. Thoshkahna · V. Sudha · K.R. Ramakrishnan ·
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    ABSTRACT: We propose a simple speech music discriminator that uses features based on HILN (harmonics, individual lines and noise) model. We have been able to test the strength of the feature set on a standard database of 66 files and get an accuracy of around 97%. We also have tested on sung queries and polyphonic music and have got very good results. The current algorithm is being used to discriminate between sung queries and played (using an instrument like flute) queries for a query by humming (QBH) system currently under development in the lab
    Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on; 06/2006

Publication Stats

5 Citations
4.63 Total Impact Points