Voiceprint Recognition System — Not Just a Powerful Authentication Tool

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Introduction

In this advanced age, when mobile Internet is the norm, people leverage social networking, online shopping and online financial transactions without the need of being physically present at places. As a result, identity authentication has become the most critical security activity in the online world. The traditional solution uses a password or a private key that you need to remember. In fact, many people prefer keeping simple passwords such as “123456” to shuttle through the Internet world. Unfortunately, this makes their online data an easy target for hackers. Traditional solutions are a risky affair as the passwords are forgotten or lost and are also prone to hacker attacks.

Solutions

Fortunately, we all have unique “living passwords” on our bodies, such as the fingerprints, face, voice, and eyes. They are the unique and distinctive characteristics of individuals popularly called “biometric signatures.” Voice is just one way of reflecting a person’s identity. In reference to the nomenclature for “fingerprint,” we also call it “voiceprint.”

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About Voiceprint Recognition System

Voiceprint refers to the acoustic frequency spectrum that carries the speech information in a human voice. Like fingerprints, it has unique biometric signatures, is individual-specific, and can function as an identification method. The acoustical signal is a unidimensional continuous signal. On discretization, you will get the acoustical signal that can be processed by conventional computers.

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Working Principle

1:1 Recognition System

The working model of this biometric identification system requires you to provide your identity (account) and biometric features beforehand and saves it as a template. During processing, the system compares the entered features with the stored biometric characteristics, to determine whether the two sets match. Such systems are popularly known as 1:1 recognition system (also called speaker verification).

1: N Recognition System

The working model of this biometric identification system doesn’t ask for biometric features before processing. It only requires the biometric features during runtime and then compares it with all the multiple records of biometric features stored in the background to determine the right match. Such systems are popularly known as 1: N recognition system (also called speaker identification).

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Voiceprint Recognition Algorithm: the Technical Details

Let’s delve a little deeper into the technical details of the voiceprint recognition algorithm. In the feature layer, the classic Mel-Frequency Cepstral Coefficients (MFCC), the Perceptual Linear Prediction (PLP), the Deep Feature, and the Power-Normalized Cepstral Coefficients (PNCC) are all outstanding acoustic features used as inputs for model learning. However, MFCC remains the most frequently used feature.

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Conclusion

In this blog, we dissected and learned the basics of the voice recognition system, the details about its underlying principles, and how it plays a significant role in biometric identification industry.

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