2011
DOI: 10.14569/ijacsa.2011.020911
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Hybrid Query by Humming and Metadata Search System (HQMS) Analysis over Diverse Features

Abstract: Abstract-Retrieval of music content over web is one of the toughest job tasks and found some of the significant challenge. Song retrieval over web is the emerging problem from the category of Music Information Retrieval. Several searching techniques related to metadata and content of song are developed and implemented. In this paper we are going to propose and evaluate a new hybrid technique for song retrieval named as "hybrid query by humming and metadata search system" (HQMS).HQMS is a hybrid model that is b… Show more

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Cited by 2 publications
(2 citation statements)
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“…For the feature extraction step, they implemented scale invariant feature transform, after this step, they applied SVM classifier and they obtained a respective recognition rate with 88.33%. Aliaa A et al [13] developed an automatic Arabic sign language (ArASL) recognition system based on the Hidden Markov Models (HMMs), they implemented a large dataset to recognize 20 isolated words from Arabic Sign Language. The approaches are experimented using real ArASL videos and reaches an accuracy of 82.22%.…”
Section: Related Workmentioning
confidence: 99%
“…For the feature extraction step, they implemented scale invariant feature transform, after this step, they applied SVM classifier and they obtained a respective recognition rate with 88.33%. Aliaa A et al [13] developed an automatic Arabic sign language (ArASL) recognition system based on the Hidden Markov Models (HMMs), they implemented a large dataset to recognize 20 isolated words from Arabic Sign Language. The approaches are experimented using real ArASL videos and reaches an accuracy of 82.22%.…”
Section: Related Workmentioning
confidence: 99%
“…-Metadatos. Tiene que ver con la recuperación de información musical usando metadatos [7], [8], [9] y [10]. -Análisis de señales acústicas.…”
Section: In T R O D U C C I ó N Lunclassified