Voice biometric systems are highly accurate but, like all biometrics, they can’t guarantee 100% success in every scenario. ValidSoft’s voice biometrics engine typically achieves 98-99% accuracy for GSM or landline transmissions, and near 100% with high-definition (wideband) data channels, such as those used on WIFI, 4G, or 5G.

Our system also integrates advanced features like Grey Zone Logic to minimize false positives and false negatives, ensuring reliability across various devices like smartphones and laptops.

Passive Enrollment happens naturally during regular interactions, such as conversations with a call center agent or an IVR system. The user doesn’t need to take any specific action to be enrolled.

Active Enrollment requires the user to repeat specific phrases or digits, typically associated with text-dependent voice biometrics.

ValidSoft supports both passive and active enrollment models, ensuring flexibility based on the application.

Using a voice recording device to playback another person’s voice is known as a Replay Attack. In many cases voice biometric engines can identify recording devices, using several techniques including detecting the absence of the highest and lowest frequencies which, though not audible to humans, are detectible to VB engines.

Additionally, the process of replaying creates distortion to audio, and, in many cases, this is detectable by ValidSoft’s replay detection algorithms. Another technique that can be applied is Identical Utterance Checking, where the VB engine checks previous authentications for being too identical to the one being analyzed. The most foolproof method is liveness checking, where a random element must be spoken, such as random digits. Recording another person’s static phrase or random phrase will not be sufficient to pass given the random nature of the challenge.

It should be noted, however, that the chances of obtaining a recording of a person’s authentication phrase for fraudulent purposes are small and not a common technique used in mass attacks, more for targeted attacks. ValidSoft’s production deployment has never been compromised by a replay attack that we have been made aware of.

Text-Dependent voice biometrics requires users to repeat specific phrases or words, often the same ones used during enrollment. This approach is ideal for secure authentication scenarios like mobile banking, where the phrase acts as a consistent identifier.

Text-Independent (also known as conversational) voice biometrics, on the other hand, does not rely on specific phrases. The system can authenticate users based on natural conversation, making it suitable for scenarios like call centers or virtual assistants, where authentication happens passively without interrupting the user experience.

Spoken Digit systems, like ValidSoft’s See-Say®, add an additional layer of security by requiring users to repeat a unique sequence of digits tied to a specific transaction. This ensures not only user identity verification but also the integrity of individual transactions, making it ideal for use cases where a high degree of security is required.

Voice biometric systems extract unique speaker-specific features from audio samples to create a “voiceprint” or “voice signature.” When a new voice sample is provided, the system compares it to the enrolled voiceprint using pattern-matching techniques to authenticate the speaker.

Voice biometrics leverages a range of features from speech. Low-level features are short segments of sound—like the unique way air flows through a speaker’s vocal tract—captured in as little as 20 milliseconds. High-level features, such as speech habits or language patterns, are derived from longer stretches of speech. While both are useful, research shows low-level features are more efficient for voice biometrics as they closely relate to the speaker’s physical attributes.