Improving Query-by-Singing/Humming by Combining Melody and Lyric Information

Wang, Chung-Che; Jang, Jyh-Shing Roger

doi:10.1109/taslp.2015.2409735

Cited by 22 publications

(15 citation statements)

References 20 publications

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“…The 2009 MIR-QbSH corpus was used as the first database [24]. It consists of 48 MIDI files that represent original melodies and 4431 singing and humming queries stored as wav files.…”

Section: Resultsmentioning

confidence: 99%

Multi-Classifier Based on a Query-by-Singing/Humming System

Nam

Park

2015

Symmetry

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Abstract:With the increase in the number of music files on various devices, it can be difficult to locate a desired file, especially when the title of the song or the name of the singer is not known. We propose a new query-by-singing/humming (QbSH) system that can find music files that match what the user is singing or humming. This research is novel in the following three ways: first, the Fourier descriptor (FD) method is proposed as the first classifier; it transforms the humming or music waveform into the frequency domain. Second, quantized dynamic time warping (QDTW) using symmetrical search space and quantized linear scaling (QLS) are used as the second and third classifiers, respectively, which increase the accuracy of the QbSH system compared to the conventional DTW and LS methods. Third, five classifiers, which include the three already mentioned along with the conventional DTW using symmetrical search space and LS methods, are combined using score level fusion, which further enhances performance. Experimental results with the 2009 MIR-QbSH corpus and the AFA MIDI 100 databases show that the proposed method outperforms those using a single classifier and other fusion methods.

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“…The 2009 MIR-QbSH corpus was used as the first database [24]. It consists of 48 MIDI files that represent original melodies and 4431 singing and humming queries stored as wav files.…”

Section: Resultsmentioning

confidence: 99%

Multi-Classifier Based on a Query-by-Singing/Humming System

Nam

Park

2015

Symmetry

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“…Most prior arts that have been published are applications relating to retrieval of musical contents. For example, the query by singing/humming (QBSH) are one of the typical topics [1,2,3]. The problem of QBSH is different from that of AMMPD.…”

Section: Related Workmentioning

confidence: 99%

Detecting and Locating Plagiarism of Music Melodies by Path Exploration Over a Binary Mask

Sie¹,

Chiang²,

Yang³

et al. 2017

Computer Science &Amp; Information Technology (CS &Amp; IT)

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“…Most prior arts that have been published are applications relating to retrieval of musical contents, such as the query by singing/humming (QBSH) systems [1,2,3]. The QBSH problem is different from the AMMPD problem.…”

Section: Related Workmentioning

confidence: 99%