Text-Dependent Speaker Recognition

Some of our service users have poor speech or no speech at all. With these service users an alternative form of communication is required or an ability to listen intently and comprehend what they are saying.

It is important to note that the main applications of biometrics are utilized for preventing fraud and ensuring security. The use of biometrics has increased tremendously but so has social, ethical, privacy, practical and even political issues associated with it (Duquenoy, Jones & Blundell, 2008). Following is the detail regarding its ethical and privacy issue implications.

Changes in the way people interact, it is changing where individuals will be spending more time face-to-face with a computer.

2) Oppose the text-to-speech feature? What markets for your work, if any, might be adversely affected?

Geometry and Algebra are so crucial to the development of the world it is taught to every public high school in the United States, around 14.8 million teenagers each year (National Center for Education Statistics). Mathematics is the engine powering our world; our stocks, economy, technology, and science are all based off from math. Math is our universal and definite language “I was especially delighted with the mathematics, on account of the certitude and evidence of their reasonings.” (Rene Descartes, 1637).

In regards to algebra the advancement math can be perceived as a puzzle. Each piece plays a detrimental role in the discovery of the bigger picture. In algebra specifically there are 3 significant stages of progress that have evolved math into what we know today. The first phase of math to be discovered was rhetorical, which was later followed by syncopated and lastly symbolic. These three stages of progression also reflect on the advancement of S.T.E.M. based careers.

The reason why it is so accurate is because the iris in human eyes is completely formed by the eighth month of a person’s life. Iris recognition can be used to identify a person of practically any age.

The technology has advanced considerably over the last few years and although still not considered the perfect security however will very likely be the method most used to positively identify an individual. The most common uses of biometrics includes characteristics found in fingerprints, face recognition, iris, signatures and even actual DNA.

Like each other part of human advancement, mathematics has its own particular birthplace focused around the needs of humanity in searching for understanding. Mathematics emerged from the necessity to quantify time and number. The earliest evidence of counting occurred in mountains of Africa were notched bones and scored pieces of wood and stone were discovered. As human advancements started to surface in Asia and the near east, frameworks and essential appreciation of arithmetic, geometry and polynomial math started to develop. Mathematics has made a lot of progress from the first evidence of counting in 50,00 B.C to the current utilization of math all over the place from cellphones and machines to dating of old ancient rarities and adjusting

The necessities of the biometric highlight utilized for confirmation reasons for existing are seven, and they need to consider for the accompanying property:

Currently, Facebook has the largest facial recognition database in the world, allowing users to tag friends in photos, identifying to their unique identity. Deborah Gonzalez, an attorney and founder of Law2sm LLC, discusses the advancement of technology if people were not afraid of this improvement. She introduces the idea of using Google Glasses, which are smart glasses, incorporated with Facebook’s facial recognition database, allowing users to find personal information about each and every person around them. Currently, India has documented personal information from 500 million citizens for biometric analysis, allowing them to manipulate the data for informative purposes, which would be extremely useful for calculating poverty percentages. However, many human rights advocates are fighting this (https://www.elsevier.com/connect/amid-rampant-data-breaches-and-hacks-biometrics-takes-off). Many of the problems seen by society are opinionated and could be very advantageous if

Human speech is the most natural form of communication and conveys both meaning and identity. The identity of a speaker can be determined from the information contained in the speech signal through speaker identification. Speaker identification is concerned with identifying unknown speakers from a database of speaker models previously enrolled in the system. Speaker (voice) identification has varied applications ranging from opening doors to security systems.

account [2]. These basic features can basically ensure that classification, but there is still much room for improvement. Therefore, some researchers have proposed some new features, such as harmony features [2]. Some researchers also consider in combination acoustic features with other speech features such as semantic features (individual keywords), and facial expression could be a good choice. Dimensionality reduction is indispensable, thus the second issue is further to get optimal features sets with minimal completeness. This stage aims to reduce the size of the extracted speech feature set by selecting the most valuable subset of features and removing the irrelevant ones. Its not easy to give universal and effec-

Biometrics is used in many places and there is a bright future for them. Coca Cola has recently replaced time card system with hand scanning machines. Finger print scanners are being used in many states of the US. They have been used to trace social welfare fraud. An iris pattern identification system is being used in Cook County, Illinois to ensure that right people are released from jail. ATM machines have been installed with finger scanners to prevent theft and fraud in Indiana (Jain, 2005).

Mel cepstral feature extraction technique is required in some or the other form in most of the latest speech and speaker recognition system. Here, first samples of speech are splitted into overlapping frames. Generally the length of frame is 25 ms and frame rate is 10 ms. Each and every frames are refined by pre-emphasis filter which amplifies higher frequencies. Next is to apply windowing so that Fourier spectrum for each windowing frame is achieved here Hamming window is used. To obtain vector of log energy, Mel spaced bank of filter is used which varies from 20 to 40 depending upon the requirement of particular application. The output of which is converted to give cepstral coefficients using DCT. Initially for computing the feature vector, 12 coefficients are obtained along with one energy make its 13 cepstral coefficient.