The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 26, 2024

Filed:

Jan. 29, 2020
Applicant:

Nippon Telegraph and Telephone Corporation, Tokyo, JP;

Inventors:

Takaaki Fukutomi, Tokyo, JP;

Takashi Nakamura, Tokyo, JP;

Kiyoaki Matsui, Tokyo, JP;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/06 (2013.01); G06N 20/00 (2019.01); G10L 21/0208 (2013.01); G10L 25/78 (2013.01); G10L 25/81 (2013.01); G10L 25/84 (2013.01); G10L 25/87 (2013.01);
U.S. Cl.
CPC ...
G10L 15/063 (2013.01); G06N 20/00 (2019.01); G10L 21/0208 (2013.01); G10L 25/78 (2013.01); G10L 25/81 (2013.01); G10L 25/84 (2013.01); G10L 25/87 (2013.01); G10L 2025/783 (2013.01); G10L 2025/786 (2013.01);
Abstract

A learning data acquisition device or the like, capable of acquiring learning data by superimposing noise data on clean voice data at an appropriate SN ratio, is provided. The learning data acquisition device includes a voice recognition influence degree calculation unit and a learning data acquisition unit. The voice recognition influence degree calculation unit calculates an influence degree on voice recognition accuracy caused by a change of a signal-to-noise ratio, based on a result of voice recognition on the knoise superimposed voice data and a result of voice recognition on the k−1noise superimposed voice data, where K is an integer of 2 or larger, k=2, 3, . . . , K, and a signal-to-noise ratio of the the knoise superimposed voice data is smaller than a signal-to-noise ratio of the k−1noise superimposed voice data, and obtains a largest signal-to-noise ratio SNRamong signal-to-noise ratios of the k−1noise superimposed voice data when the influence degree meets a given threshold condition. The learning data acquisition unit acquires noise superimposed voice data having a signal-to-noise ratio that is equal to or larger than the signal-to-noise ratio SNR, as learning data.


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