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UTD CS 6V81 - Lecture #12 Biometric Technologies: Voice Scan

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Introduction to BiometricsOutlineReferencesIntroductionIntroduction (Continued)How does it work?How does it work? (Concluded)Components of the Voice Scan SystemProcess:Distinctive FeaturesTemplate Creation/GenerationTemplate MatchingApplicationsDeploymentMarketStrengths of Voice ScanWeaknesses of Voice ScanResearch DirectionsTechnology ComparisonSummaryIntroduction to BiometricsThe ProblemThe Problem (Concluded)The SolutionThe Solution (Concluded)DetailsDetails (Continued)Slide 28Slide 29Details (Concluded)Choice of FeaturesSpoeaker ModelingSpeaker Modeling (Continued)Speaker Modeling (Concluded)Pattern MatchingIntroduction to BiometricsDr. Bhavani ThuraisinghamThe University of Texas at DallasLecture #12Biometric Technologies: Voice ScanOctober 3, 2005OutlineIntroductionHow does it workComponentsVoice Scan ProcessTemplate generation and matchingMarket and ApplicationsStrengths and WeaknessesResearch DirectionsSummaryAppendix: Banking ApplicationReferencesCourse Text Book, Chapter 7http://www.biometricsinfo.org/voicerecognition.htmIntroductionVoice Recognition is a technology which allows a user to use his/her voice as input. Voice recognition may be used to dictate text into the computer or to give commands to the computer (such as opening application programs, pulling down menus, or saving work). Older voice recognition applications require each word to be separated by a distinct space. This allows the machine to determine where one word begins and the next stops. These kinds of voice recognition applications are still used to navigate the computer's system, and operate applications such as web browsers or spread sheets.Introduction (Continued)Newer voice recognition applications allow a user to dictate text fluently into the computer. These new applications can recognize speech at up to 160 words per minute. Voice recognition uses a neural net to "learn" to recognize voice. As you speak, the voice recognition software remembers the way you say each word. This customization allows voice recognition, even though everyone speaks with varying accents and inflection. In addition to learning how you pronounce words, voice recognition also uses grammatical context and frequency of use to predict the word you wish to input. While the accuracy of voice recognition has improved users still experience problems with accuracy either because of the way they speak or the nature of their voice.How does it work?Voice recognition technology utilizes the distinctive aspects of the voice to verify the identity of individuals.Voice recognition is occasionally confused with speech recognition, a technology which translates what a user is saying (a process unrelated to authentication). Voice recognition technology, by contrast, verifies the identity of the individual who is speaking. The two technologies are often bundled – speech recognition is used to translate the spoken word into an account number, and voice recognition verifies the vocal characteristics against those associated with this account.How does it work? (Concluded)Voice recognition can utilize any audio capture device, including mobile and land telephones and PC microphones.The performance of voice recognition systems can vary according to the quality of the audio signal as well as variation between enrollment and verification devicesDuring enrollment an individual is prompted to select a passphrase or to repeat a sequence of numbers. The passphrases selected should be approximately 1-1.5 seconds in length – very short passphrases lack enough identifying data, and long passwords have too much, both resulting in reduced accuracy. The individual is generally prompted to repeat the passphrase or number set a handful of times, making the enrollment process somewhat longer than most other biometrics.Components of the Voice Scan SystemUser’s spoken phrase is converted from analog to digital formant and transmitted to local or central PCFor desktop verification applications, engine that provides templates based functions may reside on the local or central PCFor telephone based applications the software may reside in the Institution that users are interacting withVoice scan comparisons are tied directly to existing authenticating systemsMay be web-enabledProcess:Data Acquisition-Audio capture devices include mobile and land telephones and PC microphones-Individual selects a passphrase and repeats it or repeats sequence of numbers-Should be long enough-Not too loud or soft-More difficult with PC/ mobile phones than with land telephonesData Processing-The data is proceed before template creation-Eliminates gaps and performs filteringDistinctive Features Measures vocal qualities not detectable by humans-Pitch and frequency are key features measuredVoice scan algorithms also measure -gain or intensity-short time spectrum of speech, -format frequencies, -linear prediction coefficients, -cepstral coefficient-Spectrograms-Nasal coarticulationReplicable only by human voice and therefore more secureTemplate Creation/Generation Based on statistics based pattern matching called Hidden Markov Models (HMM)HMM are generalized profiles that are formed through the comparison of multiple samples to find characteristically repeating patternsDuring enrollment template generation relies on the capture of multiple voice samples and are analyzed to determine the qualities that can be relied upon for later recognitionTemplate Matching Production voice scan technologies are not capable of one-many identificationOperates in one-one authentication modeWhen user attempts verification the system compares the live submission with the profile created and then returns a statistical ratingUsers may change their speech during enrollment and verification and therefore not very reliableApplicationsVoice recognition is a strong solution for implementations in which vocal interaction is already present. It is not a strong solution when speech is introduced as a new process. Telephony is the primary growth area for voice recognition, and will likely be by far the most common area of implementation for the technology. Telephony-based applications for voice recognition include account access for financial services, customer authentication for service callsThese solutions route callers through enrollment and


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UTD CS 6V81 - Lecture #12 Biometric Technologies: Voice Scan

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