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Title:
MACHINE LEARNING APPARATUS, ANALYSIS APPARATUS, MACHINE LEARNING METHOD, AND ANALYSIS METHOD
Document Type and Number:
WIPO Patent Application WO/2019/216320
Kind Code:
A1
Abstract:
In the present invention, a biological sound is accurately extracted from noisy acoustic data. A machine learning apparatus (1) is for learning a predictive algorithm (D2) for predicting whether a biological sound is included in acoustic data. The machine learning apparatus (1) is provided with: an acoustic data acquisition unit (121) that acquires the acoustic data obtained from a subject by a sound collection device (4); a biological sound determination unit (123) that determines whether or not the biological sound is included in the acoustic data, in accordance with a user's operation; a feature amount extraction unit (124) that extracts a feature amount in the acoustic data; and a learning unit (13) that learns the predictive algorithm on the basis of the feature amount and a result of determination by the biological sound determination unit (123). The feature amount includes at least any one of PNCC, MFCC, ΔPNCC, ΔΔPNCC, ΔMFCC, ΔΔMFCC, BSF, a feature related to a formant, a feature related to a pitch, an LPC coefficient, spectrum flatness, logarithmic energy, a duration time period of a sound segment, ZCR, an index based on entropy, and the statistics thereof.

Inventors:
EMOTO TAKAHIRO (JP)
GOJIMA YUKI (JP)
SATO RYUNOSUKE (JP)
AKUTAGAWA MASATAKE (JP)
Application Number:
PCT/JP2019/018287
Publication Date:
November 14, 2019
Filing Date:
May 07, 2019
Export Citation:
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Assignee:
UNIV TOKUSHIMA (JP)
International Classes:
A61B7/04; A61B10/00; G10L25/15; G10L25/18; G10L25/24
Domestic Patent References:
WO2017135127A12017-08-10
Foreign References:
JP2015514456A2015-05-21
US20170301347A12017-10-19
Other References:
SATO, R. ET AL.: "Automatic Bowel Motility Evaluation Technique for Noncontact Sound Recordings", APPLIED SCIENCES, vol. 8, no. 999, 19 June 2018 (2018-06-19), pages 1 - 9, XP055651526
Attorney, Agent or Firm:
SAEGUSA & PARTNERS (JP)
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