Music type classification by spectral contrast feature
Automatic music type classification is very helpful for the management of digital music databases. In this paper, the octave-based spectral contrast feature is proposed to represent the spectral characteristics of a music clip. It represented the relative spectral distribution instead of average spe...
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creator | Dan-Ning Jiang Lie Lu Hong-Jiang Zhang Jian-Hua Tao Lian-Hong Cai |
description | Automatic music type classification is very helpful for the management of digital music databases. In this paper, the octave-based spectral contrast feature is proposed to represent the spectral characteristics of a music clip. It represented the relative spectral distribution instead of average spectral envelope. Experiments show that the octave-based spectral contrast feature performs well in music type classification. Another comparison experiment demonstrates that the octave-based spectral contrast feature has a better discrimination among different music types than mel-frequency cepstral coefficients (MFCC), which is often used in previous music type classification systems. |
doi_str_mv | 10.1109/ICME.2002.1035731 |
format | Conference Proceeding |
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In this paper, the octave-based spectral contrast feature is proposed to represent the spectral characteristics of a music clip. It represented the relative spectral distribution instead of average spectral envelope. Experiments show that the octave-based spectral contrast feature performs well in music type classification. 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Another comparison experiment demonstrates that the octave-based spectral contrast feature has a better discrimination among different music types than mel-frequency cepstral coefficients (MFCC), which is often used in previous music type classification systems.</description><subject>Asia</subject><subject>Cepstral analysis</subject><subject>Computer science</subject><subject>Hidden Markov models</subject><subject>History</subject><subject>Mel frequency cepstral coefficient</subject><subject>Modems</subject><subject>Multiple signal classification</subject><subject>Spatial databases</subject><subject>Technology management</subject><isbn>9780780373044</isbn><isbn>0780373049</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2002</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj8tqwzAQRQWlkJL6A0I3-gG7I40e1rKYtA0kZNHugyKPQMVNjKUs_Pc1NIcLZ3fhMLYR0AgB7nXXHbaNBJCNANQWxQOrnG1hGVoEpVasyvkHFtBp3cITM4dbToGXeSQeBp9ziin4kq4Xfp55HimUyQ88XC-Lc-GRfLlN9Mweox8yVXev2df79rv7rPfHj133tq-DNKbU1gsRJSrqndOWNDmiPkSSfYyqd1FKRAyA0vTnYECa2LZaGlLRKgu4Zi__r4mITuOUfv00n-5t-AcMwkSR</recordid><startdate>2002</startdate><enddate>2002</enddate><creator>Dan-Ning Jiang</creator><creator>Lie Lu</creator><creator>Hong-Jiang Zhang</creator><creator>Jian-Hua Tao</creator><creator>Lian-Hong Cai</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2002</creationdate><title>Music type classification by spectral contrast feature</title><author>Dan-Ning Jiang ; Lie Lu ; Hong-Jiang Zhang ; Jian-Hua Tao ; Lian-Hong Cai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c266t-7a11f234ed9957e5e9eedcfe2dff4d9f22333c0326dbc6026f88526e4f74703</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Asia</topic><topic>Cepstral analysis</topic><topic>Computer science</topic><topic>Hidden Markov models</topic><topic>History</topic><topic>Mel frequency cepstral coefficient</topic><topic>Modems</topic><topic>Multiple signal classification</topic><topic>Spatial databases</topic><topic>Technology management</topic><toplevel>online_resources</toplevel><creatorcontrib>Dan-Ning Jiang</creatorcontrib><creatorcontrib>Lie Lu</creatorcontrib><creatorcontrib>Hong-Jiang Zhang</creatorcontrib><creatorcontrib>Jian-Hua Tao</creatorcontrib><creatorcontrib>Lian-Hong Cai</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dan-Ning Jiang</au><au>Lie Lu</au><au>Hong-Jiang Zhang</au><au>Jian-Hua Tao</au><au>Lian-Hong Cai</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Music type classification by spectral contrast feature</atitle><btitle>Proceedings. 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subjects | Asia Cepstral analysis Computer science Hidden Markov models History Mel frequency cepstral coefficient Modems Multiple signal classification Spatial databases Technology management |
title | Music type classification by spectral contrast feature |
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