Verify Customers’ Identity by having them speaking a few words instead of answering questions for a frictionless authentication experience. Reduce call handle times, call center costs, and fraud attempts
Business value: Improve security and minimize breaches due to compromised passwords and phishing. Reduce threats by identifying known fraudsters. Gain customer trust and improve customer experience
Understand the Use-case under 5 minutes
Video (1.5 minutes)
See how using voice biometrics authentication can improve Customer Satisfaction, reduce fraud, reduce Operational Costs, and elevate the Customer Experience
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Video (3 minutes)
Describing (and busting) three myths related to using voice biometrics: they are too complicated, expensive, and come with painful user onboarding.
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Get to know more Business and Technical details about the use-case (15-30 minutes)
More detailed introduction covering business and technical aspects
Article (9 minutes)
Introducing the benefits of Voice Biometrics, How to implement it, what companies use them, and how to the impact these systems bring to enhancing security
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Article (9 minutes)
Artificial intelligence can analyze speech and facial characteristics to create a digital identity that allows for a much more secure online setting. It's a promising breakthrough for the financial sector.
VisitCase studies, Organizational Aspects, Return on Investment examples
Case Study (6 minutes)
About 2.8 million customers have signed up to use HSBC’s Voice ID system. It estimates that the extra layer of security has prevented £249m of UK customers’ money falling into the hands of criminals in the last year
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Case Study (8 minutes)
See how voice biometrics made authentication painless for Barclays, resulting into: 15% reduction in average call times, 93% of clients scored at least 9 out of 10 for its voice authentication system, 90% reduction in complaints regarding security service
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Case Study (8 minutes)
Tatra banka became the first bank in Slovakia as well as in Central and Eastern Europe, delivering to their clients a seamless, secure and personal authentication through voice biometrics.
VisitMore details on the technical aspects of the use-case
Video (17 minutes)
Amazon Connect Voice ID provides real-time caller authentication that makes voice interactions in contact centers more secure and efficient
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AI Service (4 minutes)
The Speaker Recognition service provides algorithms that verify and identify speakers by their unique voice characteristics using voice biometry. You will have an overview on how speaker identification works and how it will help your financial institution.
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Article (8 minutes)
This paper reviews the current state of voice recognition technology and shows how deep learning is providing the key to unlock the power of biometrics
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Technical resources that will help you implement the use-case (notebooks, tutorials..)
AI Service
The service provides algorithms that verify and identify speakers by their unique voice characteristics using voice biometry. This documentation includes how it works, getting started, & a step-by-step guide.
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Github Repo
Github repo for Voice Authentication using Microsoft speaker recognition API. In which you can find a step-by-step get started and how to run the model for speaker recognition using Microsoft Azure Store.
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GitHub Repo
VoiceSens is a text independent voice biometric solution which is developed in Python and uses Watson Speech to Text (speech recognition). Repo includes step-by-step set up and getting started as well as demo screenshots
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GitHub Repo
Implementing MFCC and GMM for Speaker Recognition. We have considered MFCC with “tuned parameters” as the primary feature and delta- MFCC as secondary feature.
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GitHub Repo
One Shot Learning using Siamese Network for Speaker Recognition
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Data Sets you can use to build Demos, POCs, or test Algorithms
an open source, multi-language dataset of voices that anyone can use to train speech-enabled applications. The dataset currently consists of 11,192 validated hours in 76 languages, but we’re always adding more voices and languages
An expanding ontology of 635 audio event classes and a collection of 2,084,320 human-labeled 10-second sound clips drawn from YouTube videos
Recordings of 630 speakers of 8 dialects of American English each reading 10 phonetically-rich sentences. It also comes with the word and phone-level transcriptions of the speech
Off-the-Shelf Products using AI for Voice Authentication
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