Title:
CROSS-LINGUAL SPEAKER RECOGNITION
Document Type and Number:
WIPO Patent Application WO/2023/076653
Kind Code:
A3
Abstract:
Disclosed are systems and methods including computing-processes executing machine-learning architectures for voice biometrics, in which the machine-learning architecture implements one or more language compensation functions. Embodiments include an embedding extraction engine (sometimes referred to as an "embedding extractor") that extracts speaker embeddings and determines a speaker similarity score for determine or verifying the likelihood that speakers in different audio signals are the same speaker. The machine-learning architecture further includes a multi-class language classifier that determines a language likelihood score that indicates the likelihood that a particular audio signal includes a spoken language. The features and functions of the machine-learning architecture described herein may implement the various language compensation techniques to provide more accurate speaker recognition results, regardless of the language spoken by the speaker.
Inventors:
KHOURY ELIE (US)
CHEN TIANXIANG (US)
KUMAR AVROSH (US)
SIVARAMAN GANESH (US)
PHATAK KEDAR (US)
CHEN TIANXIANG (US)
KUMAR AVROSH (US)
SIVARAMAN GANESH (US)
PHATAK KEDAR (US)
Application Number:
PCT/US2022/048365
Publication Date:
June 08, 2023
Filing Date:
October 31, 2022
Export Citation:
Assignee:
PINDROP SECURITY INC (US)
International Classes:
G10L25/60; G06F40/263; G06N3/02; G06N3/045; G10L17/00; G10L17/10; G10L17/26
Foreign References:
| US20210256981A1 | 2021-08-19 | |||
| US20210074295A1 | 2021-03-11 | |||
| US20210200965A1 | 2021-07-01 |
Attorney, Agent or Firm:
SOPHIR, Eric et al. (US)
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