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1. (WO2018160943) METHOD AND APPARATUS FOR DETECTING SPOOFING CONDITIONS
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Pub. No.: WO/2018/160943 International Application No.: PCT/US2018/020624
Publication Date: 07.09.2018 International Filing Date: 02.03.2018
IPC:
G10L 25/51 (2013.01) ,G10L 25/30 (2013.01) ,G10L 17/00 (2013.01)
G PHYSICS
10
MUSICAL INSTRUMENTS; ACOUSTICS
L
SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
25
Speech or voice analysis techniques not restricted to a single one of groups G10L15/-G10L21/129
48
specially adapted for particular use
51
for comparison or discrimination
G PHYSICS
10
MUSICAL INSTRUMENTS; ACOUSTICS
L
SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
25
Speech or voice analysis techniques not restricted to a single one of groups G10L15/-G10L21/129
27
characterised by the analysis technique
30
using neural networks
G PHYSICS
10
MUSICAL INSTRUMENTS; ACOUSTICS
L
SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
17
Speaker identification or verification
Applicants:
PINDROP SECURITY, INC. [US/US]; 817 W. Peachtree St., NW Suite 770 Atlanta, Georgia 30308, US
Inventors:
KHOURY, Elie; US
NAGARSHETH, Parav; US
PATIL, Kailash; US
GARLAND, Matthew; US
Agent:
SOPHIR, Eric L.; US
Priority Data:
15/910,38702.03.2018US
62/466,91103.03.2017US
Title (EN) METHOD AND APPARATUS FOR DETECTING SPOOFING CONDITIONS
(FR) PROCÉDÉ ET APPAREIL DE DÉTECTION D'ÉTATS D'ARNAQUE
Abstract:
(EN) An automated speaker verification (ASV) system incorporates a first deep neural network to extract deep acoustic features, such as deep CQCC features, from a received voice sample. The deep acoustic features are processed by a second deep neural network that classifies the deep acoustic features according to a determined likelihood of including a spoofing condition. A binary classifier then classifies the voice sample as being genuine or spoofed.
(FR) L'invention concerne un système de vérification de locuteur automatisée (ASV) qui incorpore un premier réseau neuronal profond pour extraire des caractéristiques acoustiques profondes, telles que des caractéristiques CQCC profondes, d'un échantillon vocal reçu. Les caractéristiques acoustiques profondes sont traitées par un second réseau neuronal profond qui classifie les caractéristiques acoustiques profondes selon une probabilité déterminée qu'elles comprennent un état d'arnaque. Un classificateur binaire classe ensuite l'échantillon vocal comme étant authentique ou une arnaque.
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Designated States: AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW
African Regional Intellectual Property Organization (ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Office (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (EPO) (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)
Publication Language: English (EN)
Filing Language: English (EN)