Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/8598
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dc.contributor.authorBiswas, R.
dc.contributor.authorMurthy, Y.V.S.
dc.contributor.authorKoolagudi, S.G.
dc.contributor.authorVishnu, S.G.
dc.date.accessioned2020-03-30T10:22:27Z-
dc.date.available2020-03-30T10:22:27Z-
dc.date.issued2020
dc.identifier.citationAdvances in Intelligent Systems and Computing, 2020, Vol.766, , pp.161-168en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8598-
dc.description.abstractThis paper presents�an approach for assessing the pitch in vocal monophonic music objectively using various�signal processing techniques. A database�has been collected with 250 recordings containing�both arohan and avarohan patterns rendered by 25 different singers for 10 Hindustani classical ragas. The fundamental frequency (F0) values of the user renditions are estimated and analyzed with the original pitch values to quantify the level of variations in pitch initially the five-point moving window has been considered to smoothen the contour. Later, first order and second order differential techniques are applied to estimate the note onset. This process is computationally economical when compared with the available approaches. The technique of cents has been used to evaluate the variation among the target and singing pitch as cent is a unit of the most common tuning system for quantifying intonation in equal tempered music. From this analysis, it is observed that singers with professional training have deviations within 15�20 cents, and non-musicians have deviations above 50 cents. Five expert singers rated the global pitch accuracy from the recordings and these results were found to exhibit high correlation with the system�s assessments. Such an evaluation system with quantitative analysis coupled with visual representation will greatly aid the training process of singers. � 2020, Springer Nature Singapore Pte Ltd.en_US
dc.titleObjective Assessment of Pitch Accuracy in Equal-Tempered Vocal Music Using Signal Processing Approachesen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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