Vocal Melody Extraction from Polyphonic Audio files using enhanced Cluster tracking - Vaidya, Vaaibhav
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Research Paper (postgraduate) from the year 2014 in the subject Art - Computer Art / Graphics / Art in Media, , language: English, abstract: It is a complicated and highly difficult task to determine the predominant melody from the musical performances which contain a large number of various instruments. It is one of the most challenging tasks in the field of music information retrieval and computational musicology. Over the past decade, melody extraction has emerged as an active research topic. In this paper, we are newly presenting a novel framework method which calculates and estimates…mehr

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Research Paper (postgraduate) from the year 2014 in the subject Art - Computer Art / Graphics / Art in Media, , language: English, abstract: It is a complicated and highly difficult task to determine the predominant melody from the musical performances which contain a large number of various instruments. It is one of the most challenging tasks in the field of music information retrieval and computational musicology. Over the past decade, melody extraction has emerged as an active research topic. In this paper, we are newly presenting a novel framework method which calculates and estimates predominant vocal melody in real-time by analyzing and tracking various source frequencies with the help of harmonic clusters (combs) and determining the actual predominant vocal source by using the harmonic strength of the source. Here we rely on the strong higher harmonics to estimate robustness against distortion and on the first harmonics caused due to low frequency accompaniments in a signal, in contrast to the currently existing methods which track only the pitch values. The proposed method, although on-line, is shown to significantly outperform our implementation of a state-of-the-art offline method for vocal melody extraction.