IP Verse

Deep Neural Network Based Speech Enhancement - EP3807878

The patent EP3807878 was granted to Pindrop Security on Dec 13, 2023. The application was originally filed on Jun 14, 2019 under application number EP19819546A. The patent is currently recorded with a legal status of "Granted And Under Opposition".

EP3807878

PINDROP SECURITY
Application Number
EP19819546A
Filing Date
Jun 14, 2019
Status
Granted And Under Opposition
Nov 10, 2023
Publication Date
Dec 13, 2023
External Links
Slate, Register, Google Patents

Patent Summary

Patent Family

Patent Family

Patent Oppositions

Patent oppositions filed by competitors challenge the validity of a granted patent. These oppositions are typically based on claims of prior art, lack of novelty, or non-obviousness. They are a key part of the process for determining a patent's strength and enforceability.

CompanyOpposition DateRepresentativeOpposition Status

Get instant alerts for new oppositions and patent status changes

KS HIMPPSep 13, 2024MEISSNER BOLTE PARTNERSCHAFT MBBWITHDRAWN

Patent Citations (10) New

Patent citations refer to prior patents cited during different phases such as opposition or international search.

Citation PhasePublication Number
DESCRIPTIONWO2010025805
INTERNATIONAL-SEARCH-REPORTUS2002107687
INTERNATIONAL-SEARCH-REPORTUS2016284346
INTERNATIONAL-SEARCH-REPORTUS2016322055
INTERNATIONAL-SEARCH-REPORTUS2017061978
INTERNATIONAL-SEARCH-REPORTUS2017365275
OPPOSITIONUS2016111107
OPPOSITIONUS2018040333
OPPOSITIONUS9972339
SEARCHUS2016111107

Non-Patent Literature (NPL) Citations (12) New

NPL citations refer to non-patent references such as research papers, articles, or other publications cited during examination or opposition phases.

Citation PhaseReference Text
OPPOSITION- Benesty Jacob, Jingdong Chen, Emanuël A. P. Habets, "Speech Enhancement in the STFT Domain", Speech Enhancement in the STFT Domain, Springer, (20120101), pages 1 - 110, XP093228563
OPPOSITION- Gao Tian et al, "Improving Deep Neural Network Based Speech Enhancement in Low SNR Environments", International Conference on Latent Variable Analysis and Signal Separation, Springer International Publishing, (20150101), pages 75 - 82, XP093228547
OPPOSITION- Grais, Emad M. et al, "Single-Channel Audio Source Separation Using Deep Neural Network Ensembles", AES Convention 140; May 2016, AES, 60 East 42nd Street, Room 2520 New York 10165-2520, USA, 60 East 42nd Street, Room 2520 New York 10165-2520, USA , (20160526), XP040680723
OPPOSITION- Loizou Philipos C., "SPEECH ENHANCEMENT Theory and Practice", SPEECH ENHANCEMENT Theory and Practice, CRC Press, (20130109), pages 1 - 21, XP093228559
OPPOSITION- Gao Tian et al, "A unified DNN approach to speaker-dependent simultaneous speech enhancement and speech separation in low SNR environments", Speech Communication, Elsevier science publishers , Amsterdam, NL, NL , (19000101), vol. 95, doi:10.1016/j.specom.2017.10.003, ISSN 0167-6393, pages 28 - 39, XP085288305
OPPOSITION- Xia Shasha; Li Hao; Zhang Xueliang, "Using optimal ratio mask as training target for supervised speech separation", 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), IEEE, (20171212), doi:10.1109/APSIPA.2017.8282021, pages 163 - 166, XP033315408
OPPOSITION- Zhao Yan et al, "Perceptually Guided Speech Enhancement Using Deep Neural Networks", 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, (20180415), doi:10.1109/ICASSP.2018.8462593, pages 5074 - 5078, XP033401904
OPPOSITION- Saleem Nasir et al, "Deep Neural Network based Supervised Speech Enhancement in Speech-Babble Noise", 2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS), IEEE, (20180606), doi:10.1109/ICIS.2018.8466542, pages 871 - 874, XP033404300
OPPOSITION- Xu Yong et al, "An Experimental Study on Speech Enhancement Based on Deep Neural Networks", IEEE Signal Processing Letters, IEEE, USA, USA, (20140101), vol. 21, no. 1, doi:10.1109/LSP.2013.2291240, ISSN 1070-9908, pages 65 - 68, XP055810204
OPPOSITION- Liang Shan et al, "The optimal ratio time-frequency mask for speech separation in terms of the signal-to-noise ratio", The Journal of the Acoustical Society of America, American Institute of Physics, 2 Huntington Quadrangle, Melville, NY 11747, 2 Huntington Quadrangle, Melville, NY 11747, (20131101), vol. 134, no. 5, doi:10.1121/1.4824632, ISSN 0001-4966, pages EL452 - EL458, XP093228550
SEARCH- Tian Gao ET AL, "Improving Deep Neural Network Based Speech Enhancement in Low SNR Environments", Computer vision - ECCV 2020 : 16th European conference, Glasgow, UK, August 23-28, 2020 : proceedings; Part of the Lecture Notes in Computer Science ; ISSN 0302-9743, Cham, Springer International Publishing, (20150101), vol. 9237, pages 75 - 82, doi:10.1007/978-3-319-22482-4_9, ISBN 978-3-030-58594-5, XP055635388 [Y] 3,8,15 * sections 3.1 and 3.2 *
SEARCH- ZHAO YAN ET AL, "Perceptually Guided Speech Enhancement Using Deep Neural Networks", 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, (20180415), doi:10.1109/ICASSP.2018.8462593, pages 5074 - 5078, XP033401904 [X] 1,2,4-7,10,11 * figure 1 * * section 2.2 * * section 3 * [Y] 3,8,15 [I] 9,12-14,16,17

Download Citation Report

Get a free citation report including examiner, opposition, and international search citations.

Get Citation Report

Dossier Documents

The dossier documents provide a comprehensive record of the patent’s prosecution history - including filings, correspondence, and decisions made by patent offices - and are crucial for understanding the patent’s legal journey and any challenges it may have faced during examination.

  • Date

    Description

  • Get instant alerts for new documents