{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T05:48:02Z","timestamp":1648792082388},"reference-count":0,"publisher":"Research Institute for Intelligent Computer Systems","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJC"],"abstract":"Music is basically a sound arranged in such a way to produce a harmonious and rhythmic sound. The basis of music is a tone, which is a natural sound and has different frequencies for each sound. Each constant sound represents a tone. The tones can also be represented in a chord. Humans are capable of creating a sound or imitating a tone from other human beings, but they are naturally unable to represent them into musical notation without musical instruments. This research addresses a model of Hum-to-Chord (H2C) conversion using a Chroma Feature (CF) to extract the characteristics and a Hidden Markov Model (HMM) to classify them. A 10-fold cross-validating shows that the best model is represented by the chroma coefficients of 55 and HMM with a codebook of 16, which gives an average accuracy of 94.83%. Examining on a 30% testing set proves that the best model has a high accuracy of up to 97.78%. Most errors come from the chords with both high and low octaves since they are unstable. Compared to a similar model called musical note classification (MNC), the proposed H2C model performs better in terms of both accuracy and complexity.<\/jats:p>","DOI":"10.47839\/ijc.19.4.1988","type":"journal-article","created":{"date-parts":[[2021,2,27]],"date-time":"2021-02-27T22:20:14Z","timestamp":1614464414000},"page":"555-560","source":"Crossref","is-referenced-by-count":0,"title":["HUM-TO-CHORD CONVERSION USING CHROMA FEATURES AND HIDDEN MARKOV MODEL"],"prefix":"10.47839","author":[{"given":"Hariyanto","family":"Hariyanto","sequence":"first","affiliation":[]},{"given":"Suyanto","family":"Suyanto","sequence":"additional","affiliation":[]}],"member":"27386","published-online":{"date-parts":[[2020,12,30]]},"container-title":["International Journal of Computing"],"original-title":[],"link":[{"URL":"https:\/\/computingonline.net\/computing\/article\/download\/1988\/945","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2021,2,27]],"date-time":"2021-02-27T22:20:15Z","timestamp":1614464415000},"score":1,"resource":{"primary":{"URL":"https:\/\/computingonline.net\/computing\/article\/view\/1988"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,30]]},"references-count":0,"URL":"https:\/\/doi.org\/10.47839\/ijc.19.4.1988","relation":{},"ISSN":["2312-5381","1727-6209"],"issn-type":[{"value":"2312-5381","type":"electronic"},{"value":"1727-6209","type":"print"}],"subject":[],"published":{"date-parts":[[2020,12,30]]}}}