Hierarchical filtering method for content-based music retrieval via acoustic input

Jang, Jyh-Shing Roger; Lee, Hong-Ru

doi:10.1145/500199.500201

Cited by 15 publications

(22 citation statements)

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“…The melody from acoustic input can be transcribed to a time series of pitch values by pitch tracking [4], where each pitch value corresponds to a frame (about 50ms) of the acoustic input. The pitch values are continuous and are measured in semitones and cents.…”

Section: Acoustic Melodymentioning

confidence: 99%

“…Several melody matching techniques have been proposed for content-based music retrieval [2][3][4][5][6][7]. In the earlier approaches [2,3], a melody is represented by a sequence of pitch differences between contiguous music notes, called the melody contour.…”

Section: Introductionmentioning

confidence: 99%

“…A few time series matching methods have recently been proposed for melody matching [4][5][6][7]. The melody is represented by a time series of pitch values, where accurate note segmentation is not necessary.…”

Section: Introductionmentioning

confidence: 99%

“…The melody is represented by a time series of pitch values, where accurate note segmentation is not necessary. [4,5] used dynamic time warping to do the time series matching. [6] proposed a melody skeleton technique for melody alignment and matching.…”

Section: Introductionmentioning

confidence: 99%

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Music scale modeling for melody matching

Zhu

Kankanhalli

2003

Proceedings of the Eleventh ACM International Conference on Multimedia

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Several time series matching techniques have been proposed for content-based music retrieval. These techniques represent a melody by a time series of pitch values and use time warping distance measures for melody matching. These methods have shown to be robust and effective for music retrieval by acoustic inputs, such as query-by-humming. However, due to the key transposition issue, all the current methods need to search a large space for the proper key in melody matching. This computation can be prohibitive for a practical music retrieval system with a large database.In this paper, we present a music scale modeling technique for melody matching. The root note of music scale (Major or Minor) of a melody is estimated by fitting the notes to a music scale model. The estimated root note can then be used as the key in melody matching. To the best of our knowledge, this is the first approach that utilizes music scale knowledge for retrieval. In our experiments, 96% of the songs in the database (3000 melodies) can fit into the music scale model. Promising results for query-by-humming retrieval have been obtained by using this novel approach.

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Section: Acoustic Melodymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Music scale modeling for melody matching

Zhu

Kankanhalli

2003

Proceedings of the Eleventh ACM International Conference on Multimedia

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“…This technique separates the melody alignment and melody similarity measure, difference the dynamic programming string matching methods which do it at the same time. A time series matching approach proposed in [6], [7], [21] has shown effectiveness for QbH in terms of robustness against note errors, since accurate note segmentation is not needed. The method above is based on time and frequency domain analysis which cannot be processed at the same time.…”

mentioning

confidence: 99%