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3 articles for “Music information retrieval”
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Identification of individual ragas using artificial neural network classifier
Abstract: This paper presents the feature extraction as the base step of music information retrieval. Basic feature of music is chroma, which is extracted using from the music signal using spectrogram and chromagram. After the extraction of feature the comparison is made between the original data and extracted chroma data using neural network. Cite this ArticlePriya, Ravi Kumar. Identification of individual ragas using artificial neural network classifier. Journal of Artificial Intelligence …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 2, Issue 2, 2015 · pp. 24–28 Read article
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Melody Extraction from Polyphonic Music Using Deep Neural Network: A Literature Survey
Abstract: Abstract: Melody extraction plays an important role in the field of Music Information Retrieval (MIR). It has emerged as one of the active research problems in the MIR applications. Nowadays, the music providers have to facilitate searching of music based on their contents or recommend music based on user’s interest having similar contents. Melody extraction is necessary to fulfil these user-interest driven searching and recommendation. The main objective of melody …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 3, 2019 · pp. 16–21 Read article
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Note Repositioning Algorithm for Musical Instruments in Indian Classical Music
Abstract: Abstract: Indian classical music has two broad aspects; the vocalists and the instrumentalists. The vocalists are often accompanied by the instrumentalists who follow the singing of the vocalists. To produce enriching and pleasant music, the instrumentalist has to match the tonal quality of vocalist. This can be achieved by the instrumentalist repositioning the notes played on his instrument. The instrumentalist has to play the same music on different notes, which …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 3, 2019 · pp. 22–27 Read article