Implementation of a matching engine for a practical query-by-singing/humming system

Jang, Dalwon; Song, Chai-Jong; Shin, Saim; Park, Sung‐Joo; Jang, Sei-Jin; Lee, Seok-Pil

doi:10.1109/isspit.2011.6151570

Cited by 9 publications

(17 citation statements)

References 20 publications

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“…In a different approach the melody may be represented in the form of relative changes of consecutive pitches (differential/delta representation) (Jang et al, 2011). This eliminates the problem but representing raw pitch vectors in this form often yields poor results.…”

Section: Melody Matchingmentioning

confidence: 99%

“…The query may be transposed by, e.g., all possible numbers of semitones within the octave (Yu et al, 2008) or from −5 to +5 semitones in half-of-the-semitone steps (Jang et al, 2011). Various numbers of repetitions may be considered but in any way this is clearly a brute-force approach which increases the computational complexity significantly.…”

Section: Melody Matchingmentioning

confidence: 99%

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Follow That Tune-Adaptive Approach to DTW-based Query-by-Humming System

Stasiak¹

2015

Archives of Acoustics

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Dynamic Time Warping is a standard algorithm used for matching time series irrespective of local tempo variations. Its application in the context of Query-by-Humming interface to multimedia databases requires providing the transposition independence, which involves some additional, sometimes computationally expensive processing and may not guarantee the success, e.g., in the presence of a pitch trend or accidental key changes.The method of tune following, proposed in this paper, enables solving the pitch alignment problem in an adaptive way inspired by the human ability of ignoring typical errors occurring in sung melodies. The experimental validation performed on the database containing 4431 queries and over 5000 templates confirmed the enhancement introduced by the proposed algorithm in terms of the global recognition rate.

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Section: Melody Matchingmentioning

confidence: 99%

Section: Melody Matchingmentioning

confidence: 99%

Follow That Tune-Adaptive Approach to DTW-based Query-by-Humming System

Stasiak¹

2015

Archives of Acoustics

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“…This paper presents the test results of the QbSH system proposed in [24] depending on the pitch extraction algorithm. In our previous works, we developed a query-by-singing/ humming (QbSH) system of which database is constructed from polyphonic recordings such as MP3 files.…”

Section: Introductionmentioning

confidence: 99%

“…Use of the music DB makes the system more practical since it saves the trouble of gathering MIDI files. In [24], we proposed the matching engine of QbSH system with the assumption that we can use any pitch extraction algorithm previously reported. To verify the assumption, we tested the performance of the QbSH system varying pitch extraction algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Test of pitch extraction algorithms for query-by-singing/humming system

Jang

Lee

2012

IEEE International Symposium on Broadband Multimedia Systems and Broadcasting

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This paper presents the test results of the Queryby-singing/humming(QbSH) system, which are measured with varying the pitch extraction algorithm. The test is for verifying matching engine of our QbSH system of which database is constructed from polyphonic recordings such as MP3 files. For the test, we used 3 different pitch extraction algorithms, and the experimental results are obtained with our matching engine. From the results, we can conclude that our matching engine works well with any pitch extraction algorithm.

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Very short feature vector for music genre classiciation based on distance metric lerning

Jang

2014

2014 International Conference on Audio, Language and Image Processing

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In our study, a very short feature vector, obtained from low dimensional projection and already developed audio features, is used for music genre classification problem. A long feature vector based on the concatenation of various features is generally used in music genre classification system. Our objective is to find a short feature vector, and we applied a distance metric learning algorithm in order to reduce the dimensionality of feature vector with a little performance degradation. In our experiments based on two widely-used dataset, dimension reduction based on distance metric learning is very effective, and we can get over 80% of accuracy with only 10-dimensional feature vector.

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Implementation of a matching engine for a practical query-by-singing/humming system

Cited by 9 publications

References 20 publications

Follow That Tune-Adaptive Approach to DTW-based Query-by-Humming System

Follow That Tune-Adaptive Approach to DTW-based Query-by-Humming System

Test of pitch extraction algorithms for query-by-singing/humming system

Very short feature vector for music genre classiciation based on distance metric lerning

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