• Title/Summary/Keyword: Music Information Retrieval

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How Query by humming, a Music Information Retrieval System, is Being Used in the Music Education Classroom

  • Bradshaw, Brian
    • Journal of Multimedia Information System
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    • v.4 no.3
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    • pp.99-106
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    • 2017
  • This study does a qualitative and quantitative analysis of how music by humming is being used by music educators in the classroom. Music by humming is part division of music information retrieval. In order to define what a music information retrieval system is first I need to define what it is. Berger and Lafferty (1999) define information retrieval as "someone doing a query to a retrieval system, a user begins with an information need. This need is an ideal document- perfect fit for the user, but almost certainly not present in the retrieval system's collection of documents. From this ideal document, the user selects a group of identifying terms. In the context of traditional IR, one could view this group of terms as akin to expanded query." Music Information Retrieval has its background in information systems, data mining, intelligent systems, library science, music history and music theory. Three rounds of surveys using question pro where completed. The study found that there were variances in knowledge, training and level of awareness of query by humming, music information retrieval systems. Those variance relationships where based on music specialty, level that they teach, and age of the respondents.

Analysis of Pre-Processing Methods for Music Information Retrieval in Noisy Environments using Mobile Devices

  • Kim, Dae-Jin;Koo, Ddeo-Ol-Ra
    • International Journal of Contents
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    • v.8 no.2
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    • pp.1-6
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    • 2012
  • Recently, content-based music information retrieval (MIR) systems for mobile devices have attracted great interest. However, music retrieval systems are greatly affected by background noise when music is recorded in noisy environments. Therefore, we evaluated various pre-processing methods using the Philips method to determine the one that performs most robust music retrieval in such environments. We found that dynamic noise reduction (DNR) is the best pre-processing method for a music retrieval system in noisy environments.

A Comparative Analysis of Music Similarity Measures in Music Information Retrieval Systems

  • Gurjar, Kuldeep;Moon, Yang-Sae
    • Journal of Information Processing Systems
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    • v.14 no.1
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    • pp.32-55
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    • 2018
  • The digitization of music has seen a considerable increase in audience size from a few localized listeners to a wider range of global listeners. At the same time, the digitization brings the challenge of smoothly retrieving music from large databases. To deal with this challenge, many systems which support the smooth retrieval of musical data have been developed. At the computational level, a query music piece is compared with the rest of the music pieces in the database. These systems, music information retrieval (MIR systems), work for various applications such as general music retrieval, plagiarism detection, music recommendation, and musicology. This paper mainly addresses two parts of the MIR research area. First, it presents a general overview of MIR, which will examine the history of MIR, the functionality of MIR, application areas of MIR, and the components of MIR. Second, we will investigate music similarity measurement methods, where we provide a comparative analysis of state of the art methods. The scope of this paper focuses on comparative analysis of the accuracy and efficiency of a few key MIR systems. These analyses help in understanding the current and future challenges associated with the field of MIR systems and music similarity measures.

A Robust Content-Based Music Retrieval System

  • Lee Kang-Kyu;Yoon Won-Jung;Park Kyu-Sik
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.229-232
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    • 2004
  • In this paper, we propose a robust music retrieval system based on the content analysis of music. New feature extraction method called Multi-Feature Clustering (MFC) is proposed for the robust and optimum performance of the music retrieval system. It is demonstrated that the use of MFC significantly improves the system stability of music retrieval with better classification accuracy.

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A Study on the Retrieval Speed Improvement from Content-Based Music Information Retrieval System (내용기반 음악 검색 시스템에서의 검색 속도 향상에 관한 연구)

  • Yoon Won-Jung;Park Kyu-Sik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.1 s.307
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    • pp.85-90
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    • 2006
  • In this paper, we propose the content-based music information retrieval system with improved retrieval speed and stable performance while maintaining resonable retrieval accuracy In order to solve the in-stable system problem multi-feature clustering (MFC) is used to setup robust music DB. In addition, the music retrieval speed was improved by using the Superclass concept. Effectiveness of the system with SuperClass and without SuperClass is compared in terms of retrieval speed, accuracy and retrieval precision. It is demonstrated that the use of WC and Superclass substantially improves music retrieval speed up to $20\%\~40\%$ while maintaining almost equal retrieval accuracy.

Massive Music Resources Retrieval Method Based on Ant Colony Algorithm

  • Yun Meng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.5
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    • pp.1208-1222
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    • 2024
  • Music resources are characterized by quantization, diversification and complication. With the rapid increase of the demand for music resources, the storage of music resources is very large. In order to improve the retrieval effect of music resources, a massive music resources retrieval method based on ant colony algorithm is proposed to effectively use music resources. This paper constructs autocorrelation function to extract pitch feature of music resource, classifies the music resource information by calculating feature similarity. Using ant colony algorithm to correlate the feature of music resource, gain the result of correlative, locate the result of detection and get the result of multi-module. Simulation results show that the proposed method has high precision and recall, short retrieval time and can effectively retrieve massive music resources.

A Content-Based Music Retrieval Algorithm Using Melody Sequences (멜로디 시퀸스를 이용하는 내용 기반 음악 검색 알고리즘)

  • 위조민;구경이;김유성
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10a
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    • pp.250-252
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    • 2001
  • With the growth in computer and network technologies, some content-based music retrieval systems have been developed. However, their retrieval efficiency does not satisfy user's requirement yet. Of course users hope to have a more efficient and higher precision for music retrieval. In this paper so for these reasons, we Propose an efficient content-based music retrieval algorithm using melodies represented as music sequences. From the experimental result, it is shown that the proposed algorithm has higher exact rate than the related algorithms.

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A Similarity Computation Algorithm Based on the Pitch and Rhythm of Music Melody (선율의 음높이와 리듬 정보를 이용한 음악의 유사도 계산 알고리즘)

  • Mo, Jong-Sik;Kim, So-Young;Ku, Kyong-I;Han, Chang-Ho;Kim, Yoo-Sung
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.12
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    • pp.3762-3774
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    • 2000
  • The advances of computer hardware and information processing technologies raise the needs of multimedia information retrieval systems. Up to date. multimedia information systems have been developed for text information and image information. Nowadays. the multimedia information systems for video and audio information. especially for musical information have been grown up more and more. In recent music information retrieval systems. not only the information retrieval based on meta-information such like composer and title but also the content-based information retrieval is supported. The content-based information retrieval in music information retrieval systems utilize the similarity value between the user query and the music information stored in music database. In tbis paper. hence. we developed a similarity computation algorithm in which the pitches and lengths of each corresponding pair of notes are used as the fundamental factors for similarity computation between musical information. We also make an experiment of the proposed algorithm to validate its appropriateness. From the experimental results. the proposed similarity computation algorithm is shown to be able to correctly check whether two music files are analogous to each other or not based on melodies.

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Same music file recognition method by using similarity measurement among music feature data (음악 특징점간의 유사도 측정을 이용한 동일음원 인식 방법)

  • Sung, Bo-Kyung;Chung, Myoung-Beom;Ko, Il-Ju
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.3
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    • pp.99-106
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    • 2008
  • Recently, digital music retrieval is using in many fields (Web portal. audio service site etc). In existing fields, Meta data of music are used for digital music retrieval. If Meta data are not right or do not exist, it is hard to get high accurate retrieval result. Contents based information retrieval that use music itself are researched for solving upper problem. In this paper, we propose Same music recognition method using similarity measurement. Feature data of digital music are extracted from waveform of music using Simplified MFCC (Mel Frequency Cepstral Coefficient). Similarity between digital music files are measured using DTW (Dynamic time Warping) that are used in Vision and Speech recognition fields. We success all of 500 times experiment in randomly collected 1000 songs from same genre for preying of proposed same music recognition method. 500 digital music were made by mixing different compressing codec and bit-rate from 60 digital audios. We ploved that similarity measurement using DTW can recognize same music.

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Feature Transformation based Music Retrieval System

  • Heo, Jung-Im;Yang, Jin-Mo;Kim, Dong-Hyun;Yoon, Kyoung-Ro;Kim, Won-Il
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.3
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    • pp.192-195
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    • 2008
  • People have tendency of forgetting music title, though they easily remember particular part of music. If a music search system can find the title through a part of melody, this will provide very convenient interface to users. In this paper, we propose an algorithm that enables this type of search using feature transformation function. The original music is transformed to new feature information with sequential melodies. When a melody that is a part of search music is given to the system, the music retrieval system searches the music similar to the feature information of the melody. Moreover, this transformation function can be easily extended to various music recognition systems.