In May it was announced Speaker recognition thesis Barclays Wealth was to use passive speaker recognition to verify the identity of telephone customers within 30 seconds of normal conversation. Noise reduction algorithms can be employed to improve accuracy, but incorrect application can have the opposite effect.
In text independent systems both acoustics and speech analysis techniques are used. Text-independent systems are most often used for speaker identification as they require very little if any cooperation by the speaker. 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.
Capture of the biometric is seen as non-invasive. The technology traditionally uses existing microphones and voice transmission technology allowing recognition over long distances via ordinary telephones wired or wireless. Speaker verification is usually employed as a "gatekeeper" in order to provide access to a secure system e.
N match where the voice is compared against N templates. Performance degradation can result from changes in behavioural attributes of the voice and from enrollment using one telephone and verification on another telephone "cross channel".
Speaker recognition systems fall into two categories: For identification systems, the utterance Speaker recognition thesis compared against multiple voice prints in order to determine the best match es while verification systems compare an utterance against a single voice print.
From a security perspective, identification is different from verification. In addition, the use of shared-secrets e. For example, presenting your passport at border control is a verification process: Applications[ edit ] The first international patent was filed incoming from the telecommunication research in CSELT  Italy by Michele Cavazza and Alberto Ciaramella as a basis for both future telco services to final customers and to improve the noise-reduction techniques across the network.
Spectral features are predominantly used in representing speaker characteristics. The private banking division of Barclays was the first financial services firm to deploy voice biometrics as the primary means to authenticate customers to their call centers.
Some systems also use "anti-speaker" techniques, such as cohort modelsand world models. Some systems adapt the speaker models after each successful verification to capture such long-term changes in the voice, though there is debate regarding the overall security impact imposed by automated adaptation.
In this case the text during enrollment and test is different. In forensic applications, it is common to first perform a speaker identification process to create a list of "best matches" and then perform a series of verification processes to determine a conclusive match.
Integration with two-factor authentication products is expected to increase. In a text-dependent system, prompts can either be common across all speakers e. In the verification phase, a speech sample or "utterance" is compared against a previously created voice print. If the speaker claims to be of a certain identity and the voice is used to verify this claim, this is called verification or authentication.
Conversely, a police officer comparing a sketch of an assailant against a database of previously documented criminals to find the closest match es is an identification process.1 study of speaker recognition systems a thesis submitted in partial fulfilment of the requirements for bachelor in technology in electronics & communication.
thesis w e de ned con dence measures for statistical mo deling tec hniques used in sp eec h/sp eak er recognition systems. F or sp eec h recognition w e tested a v Thesis Outline.
2 2 Sp eec h Recognition 4 What is Sp eec h?. 4 Sp eec h Comm unication b et w een Humans. 7 Hearing. 9 De nition of Sp eec h. The work leading to this thesis has been focused on establishing a text-independent closed-set speaker recognition system.
Contrary to other recognition systems, this system was built with two parts for the purpose of improving the recognition accuracy. The first part is the speaker pruning performed by KNN algorithm. Speaker Recognition. issue in speaker recognition ﬁeld.
In this thesis, our main focus is to improve the robustness of speaker recognition systems on We also built systems that support robust speaker recognition. We implemented a speaker segmentation and clustering system aiming at improving the robustness.
Speaker recognition is the identification of a person from characteristics of voices Phd thesis, Lund University. Md Sahidullah (), Enhancement of Speaker Recognition Performance Using Block Level, Relative and Temporal Information of Subband Energies, PhD thesis, Indian Institute of Technology Kharagpur.
Speaker Recognition is the art of recognizing a speaker from a given database using speech as the only input. In this thesis we will be discussing a novel approach to detect.Download