Please wait a minute...
New Technology of Library and Information Service  2004, Vol. 20 Issue (1): 41-45    DOI: 10.11925/infotech.1003-3513.2004.01.09
Current Issue | Archive | Adv Search |
Study on the Melody Based Retrieval of Music——Input Recognition of Melodic Features
Jin Yi   Huang Min
(Institute of Information Science and Technology,Shanghai Jiaotong University,Shanghai 200030,China)
Download: PDF (0 KB)  
Export: BibTeX | EndNote (RIS)      

This paper studies the input recognition and extraction of melodic features. An idea system should include textual, graphical and audio input to meet the needs of users with different levels. The model of input recognition and extraction of melodic features is also proposed.

Key wordsMusic retrieval      Music melody      Feature extraction      Melody input     
Received: 16 June 2003      Published: 25 January 2004


Corresponding Authors: Jin Yi     E-mail:
About author:: Jin Yi,Huang Min

Cite this article:

Jin Yi,Huang Min. Study on the Melody Based Retrieval of Music——Input Recognition of Melodic Features. New Technology of Library and Information Service, 2004, 20(1): 41-45.

URL:     OR

3Themefinder Help. (Accessed Sept. 4, 2003)
4胡光锐. 语音处理与识别. 上海:上海科学技术文献出版社,1994
5Lie Lu, Hong You and Hong-Jiang Zhang. A New Approach to Query By Humming in Music Retrieval.IEEE International Conference on Multimedia and Expo (ICME 2001), Waseda University, Tokyo, Japan, August 2001:22-25
6Rodger  Mcnab, Lloyd  Smith. The New Zealand Digital Library MELody inDEX. D-Lib Magazine, May 1997
7Parsons, D.The Directory of Tunes and Musical Themes.Cambridge: Spencer Brown. 1991
8E.Wold and T.Blum.Classification,Search and Retrieval of Audio. (Accessed Sept. 4, 2003)

[1] Hui Nie,Huan He. Identifying Implicit Features with Word Embedding[J]. 数据分析与知识发现, 2020, 4(1): 99-110.
[2] Gang Li,Huayang Zhou,Jin Mao,Sijing Chen. Classifying Social Media Users with Machine Learning[J]. 数据分析与知识发现, 2019, 3(8): 1-9.
[3] Xiaofeng Li,Jing Ma,Chi Li,Hengmin Zhu. Identifying Commodity Names Based on XGBoost Model[J]. 数据分析与知识发现, 2019, 3(7): 34-41.
[4] Jiao Yan,Jing Ma,Kang Fang. Computing Text Semantic Similarity with Syntactic Network of Co-occurrence Distance[J]. 数据分析与知识发现, 2019, 3(12): 93-100.
[5] Qinghong Zhong,Xiaodong Qiao,Yunliang Zhang,Mengjuan Weng. Cross-media Fusion Method Based on LDA2Vec and Residual Network[J]. 数据分析与知识发现, 2019, 3(10): 78-88.
[6] Guijun Yang,Xue Xu,Fuqiang Zhao. Predicting User Ratings with XGBoost Algorithm[J]. 数据分析与知识发现, 2019, 3(1): 118-126.
[7] Zhou Lixin,Lin Jie. Extracting Product Features with NodeRank Algorithm[J]. 数据分析与知识发现, 2018, 2(4): 90-98.
[8] Huang Xiaoxi,Li Hanyu,Wang Rongbo,Wang Xiaohua,Chen Zhiqun. Recognizing Metaphor with Convolution Neural Network and SVM[J]. 数据分析与知识发现, 2018, 2(10): 77-83.
[9] Li Weiqing,Wang Weijun. Building Product Feature Dictionary with Large-scale Review Data[J]. 数据分析与知识发现, 2018, 2(1): 41-50.
[10] Li Changbing,Pang Chongpeng,Li Meiping. Extracting Product Features with Weight-based Apriori Algorithm[J]. 数据分析与知识发现, 2017, 1(9): 83-89.
[11] Du Siqi, Li Honglian, Lv Xueqiang. Research of Chinese Chunk Parsing in Application of the Product Feature Extraction[J]. 现代图书情报技术, 2015, 31(9): 26-30.
[12] Lu Yonghe, Liang Minghui. Improvement of Text Feature Extraction with Genetic Algorithm[J]. 现代图书情报技术, 2014, 30(4): 48-57.
[13] Tang Xiaobo, Xiao Lu. Research of Text Feature Extraction on Dependency Parsing Network[J]. 现代图书情报技术, 2014, 30(11): 31-37.
[14] You Guirong, Wu Wei, Qian Yuntao. Feature Extraction Method for Detecting Spam in Electronic Commerce[J]. 现代图书情报技术, 2014, 30(10): 93-100.
[15] Xu Jian, Wen Haosheng. Study on Talents Description Web Page Automatic Recognition System[J]. 现代图书情报技术, 2011, 27(6): 20-26.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938