What is Voice Biometrics

Voice biometrics is the science of using a person’s voice as a uniquely identifying biological characteristic in order to authenticate them. Also referred to as voice verification or speaker recognition, voice biometrics enables fast, frictionless and highly secure access for a range of use cases from call center, mobile and online applications to chatbots, IoT devices and physical access.

Massive advances in neural networks over the past 2-3 years have enabled the development of voice biometric algorithms that are faster, more accurate, and can authenticate users with a smaller amount of speech. In fact, ID R&D is now able to exceed the accuracy of a 4-digit PIN in many use cases.

Like other biometric modalities, voice biometrics offer significant security advantages over authentication methods that are based on something you know (like a password or answer to a “secret” question) or something you have (like your mobile phone). Voice biometrics also improves the customer experience by removing frustration associated cumbersome login processes and lost and stolen credentials.

There are over 70 body parts– each with a unique size and shape – that contribute to how a person speaks.

Voice biometric systems work by creating a voice print or “template” of a person’s speech. A template is created, encrypted and stored for future voice verification only when a user opts in or “enrolls”. Typically, the enrollment process is passive, meaning a template can be created in the background during a user’s normal interaction with an application or agent.

The use of voice biometrics for authentication is increasing in popularity due to improvements in accuracy, fueled largely by advances in AI, and heightened customer expectations for easy and fast access to information. Frequent password-associated data breaches are another reason for broader adoption as companies look for ways to better protect customer data.

When it comes to accuracy, it’s not just about keeping the wrong person out. Companies also have to minimize “false rejects” that cause headaches for existing customers and agents. “Equal Error Rate” (EER) s is the point where the number of false accepts and false rejects is equal. Of course the goal is to make both of these error types extremely small, ideally not allowing any impostors through with only a negligible number of valid people getting rejected.

IDVoice by ID R&D is a robust AI-driven voice biometric engine that provides both text dependent and text independent voice verification for mobile web and telephone channels, as well as physical access. The product is built on an innovative Convolutional Neural Network and advanced modified x-vector approach for feature extraction technology for unmatched accuracy and is ranked #1 in the industry’s leading benchmark challenge.

IDVoice is language independent, works with ultra-short utterances and has the smallest footprint available. Download the IDVoice product collateral or visit our IDVoice Text Dependent Verification and IDVoice Text Independent Verification pages to learn more.