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Speaker recognition
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==Variants of speaker recognition== Each speaker recognition system has two phases: enrollment and verification. During enrollment, the speaker's voice is recorded and typically a number of features are extracted to form a voice print, template, or model. In the verification phase, a speech sample or "utterance" is compared against a previously created voice print. For identification systems, the utterance is compared against multiple voice prints in order to determine the best match(es) while verification systems compare an utterance against a single voice print. Because of the process involved, verification is faster than identification. Speaker recognition systems fall into two categories: text-dependent and text-independent.<ref>{{cite web | title=Speaker Verification: Text-Dependent vs. Text-Independent | website=Microsoft Research | date=2017-06-19 | url=https://www.microsoft.com/en-us/research/project/speaker-verification-text-dependent-vs-text-independent/ |quote=text-dependent and text-independent speaker .. both equal error rate and detection ..}}</ref> Text-dependent recognition requires the text to be the same for both enrollment and verification.<ref>{{cite book | last=Hébert | first=Matthieu | series=Springer Handbooks | title=Springer Handbook of Speech Processing | chapter=Text-Dependent Speaker Recognition | publisher=Springer Berlin Heidelberg | publication-place=Berlin, Heidelberg | year=2008 | isbn=978-3-540-49125-5 | issn=2522-8692 | doi=10.1007/978-3-540-49127-9_37 | pages=743–762|quote=task .. verification or identification}}</ref> In a text-dependent system, prompts can either be common across all speakers (e.g. a common pass phrase) or unique. In addition, the use of shared-secrets (e.g.: passwords and PINs) or knowledge-based information can be employed in order to create a [[multi-factor authentication]] scenario. Conversely, text-independent systems do not require the use of a specific text. They are most often used for speaker identification as they require very little if any cooperation by the speaker. In this case the text during enrollment and test is different. In fact, the enrollment may happen without the user's knowledge, as in the case for many forensic applications. As text-independent technologies do not compare what was said at enrollment and verification, verification applications tend to also employ [[speech recognition]] to determine what the user is saying at the point of authentication.{{citation needed|date=July 2022}} In text independent systems both [[acoustics]] and [[speech analysis]] techniques are used.<ref>{{cite web | last=Myers | first=Lisa | title=An Exploration of Voice Biometrics | website=SANS Institute | date=2004-07-25 | url=https://www.sans.org/white-papers/1436/ }}</ref>
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