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Glossary of Key Terms
Like many other technologies and disciplines, voice biometric systems and their related telephony applications make use of a number of techical terms and abbreviations that are not readily recognizable or understood. We've made reference to many of these terms and abbreviations throughout the website. Below is a simple list of definitions. For additional details on any of these terms, you may consider doing a Google search or perhaps consulting Wikipedia.
Biometrics. 'Biometrics' as a term refers to the measurement of a physical feature or repeatable action of an individual. There are many forms of biometric measurements taken. For example: fingerprints, retinal/iris scans, facial recognition, hand geometry, signatures, DNA, and of course voiceprints. Voice biometrics is simply a reference to the study and measurement of how individuals speak.
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Enrollment. This is the initial process of collecting data. In the case of voice biometrics, enrollment is the capture of voice samples from an individual with the intent of creating a voiceprint from the unique characteristics (or features) of their speech patterns. Enrollment can be active and voluntary or passive and involuntary.
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Equal Error Rate (EER). This is the most common term used to judge the accuracy of biometric and other security systems. The equal error rate (or EER) of any security tool is simply the operating point where the percentage of false acceptances is equal to the percentage of false rejections. The lower the EER value, the better, as it is desireable to be both very good at recognizing valid system users as well as very good at screening out imposters and fraudsters.
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False-Acceptance Rate (FAR). In biometric and other security systems, the false acceptance rate (or FAR) is the percentage of times when the system will incorrectly let an imposter or fraudster in as a valid user. This scenario is sometimes also referred to as a 'Type II' error. Giving unauthorized users access to any system can have profound implications, so it is very important to tune biometric systems to low FAR levels.
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False-Rejection Rate (FRR). In biometric and other security systems, the false rejection rate (or FRR) is the percentage of times when the system will incorrectly reject a valid user. This scenario is sometimes also referred to as a 'Type I' error. Rejecting a valid user is an inconvenience and this can have implications for long-term user acceptance. To help manage these types of errors, tuning is recommended, along with offering retries for users that 'pass' other security factors.
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Feature Extraction. When audio samples are submitted to a voice biometric engine during enrollment, verification, or identification, unique vocal characteristics are captured from the audio source(s) using sophisticated audio signal processing software. These characteristics are then analyzed and a voice model (or voiceprint) is created. This process to capture unique vocal characteristics is commonly referred to as 'feature extraction'.
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Interactive Voice Response (IVR). Interactive voice response, or IVR, refers to telephony technology in which someone uses a telephone to interact with an application or database system. IVR technology does not require that a live person answer the phone; in fact, IVR systems allow for callers to answer questions or navigate menus using either a touch-tone phone, their voices, or a combination of both. IVR systems are very common -- they are prevalent in almost every industry. Voice biometric authentication within IVR systems is a growing topic of interest, as fraud committed in IVR systems in on the rise in many industries.
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Multi-Factor Authentication (MFA). An authentication factor refers to a piece of information and/or a technique used to authenticate someone's identity. Factors are something you have (like a picture ID or token), something you know (like a password, PIN, or answer to a shared secret), or something you are (such as a biometric -- fingerprint, voiceprint, etc). Multi-Factor Authentication, or MFA, is a system where multiple factors are obtained during a session to authenticate an individual, yielding greater match probabilities.
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Speech Recognition (ASR). Speech recognition is also referred to as voice recognition or automatic speech recognition (ASR). ASR is a technology where spoken words are recognized for specific content. This technology is typically used in call centers and IVR systems. Essentially, a caller speaks when prompted, then his or her response is captured and converted to an electronic format. The electronic content is processed and transformed into patterns that are identified by a computer system as specific words. Based on the content identified, the computer system typically takes some kind of action. As an example ... please say 'sales' to speak with a sales agent or 'tech support' to get technical support, etc.
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Text-Dependent System. A text-dependent voice biometric system prompts users to speak specific words, phrases, or numbers -- placing known limits on what can be said. These same limits are then imposed during all enrollment, verification, and identification processes. Text-dependent systems tend to be easy to understand and use due to these constraints. Also, they are often less expensive to build, operate, and maintain.
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Text-Independent System. A text-independent voice biometric system does not require users to say specific words, phrases, or numbers -- almost any speech can be used. However, the enrollment process for text independent systems typically needs to be longer than text dependent systems, as more speech is needed to create a more "complete" voiceprint for users. And although setup, operating, and maintenance costs can be higher for these systems, developers appreciate the high levels of flexility possible in VUI designs.
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Text-to-Speech (TTS). The term 'text-to-speech' (or TTS) refers to speech synthesis, or a process where a computer converts written text into spoken voice output. Early TTS systems were developed to aid the visually impaired by offering them computer-generated speech that would 'read' text passages to them. Today, TTS technology is widely used within IVRs and call centers to dynamically generate and speak information to callers.
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Voice Verification. Voice verification, or voice authentication, or speaker verification refers to the process of verifying someone's identity by the use of their unique vocal characteristics. In a voice verification system, users make an initial claim of identity (perhaps by entering a user id and password to a web-based system, or by keying in a partial account number with their telephone keypad). The system then prompts them for an audio sample, processes it into a temporary voiceprint and then compares it to the stored voiceprint for that user. If the score threshold for a match is exceeded, then the user is 'passed' and may proceed ahead within the system.
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Voiceprint. A voiceprint is a mathematical representation of the unique physiological and behavioral features of a person's voice stored in electronic format (frequently properietary). A voiceprint is not a recording or file that can be played back or otherwise listened to. Rather, a voiceprint is derived from audio analysis, analog and digital filtering and compression, and statistical modeling of vocal features. Voiceprints cannot be reverse-engineered back into original speech, so this gives voiceprints very high innate security levels relative to information storage concerns.
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VoiceXML. VoiceXML is a voice-based Extensible Markup Language that has fast become the de-facto standard within call centers and IVR systems. Specifically, VoiceXML is a standard used for specifying interactive voice dialogs between people and computing systems. It does not require specific hardware to run, nor does it require proprietary extensions for any of the major telephone systems providers. Today, literally tens of millions of calls are handled each and every day by VoiceXML-based IVR systems and the numbers are growing rapidly.
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