Abstract: Temporomandibular Joint (TMJ) is one of the most frequently used joints in the human body. (Hoppenfeld, 1976) It is used when speaking, yawning, chewing, swallowing and other activities during the day and even in sleep. The frequency of movement is assessed as approximately 1500 - 2000 times a day (Magee, 2002). It is articulate between the condyle of the mandible and the squamous portion of the temporal bone. These two osseous elements are enclosed into a fibrous capsule and articulate with each other by an interposed disc of connective tissue (Haskin CL 1995).

• Publication Date: 03-Sep-2017
• DOI: 10.15224/978-1-63248-130-6-03
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Abstract: The article investigates the possibilities of applying machine learning algorithm to identify an individual through biometric voice recognition with the higher possible reliability . The emphasis in the analysis is placed on the possibility of using artificial intelligence approach methods for the purposes of recognizing a person unambiguously, uniquely on the basis of the data contained in his /her vocal spectral information . A large number of routes we can go to parametrically representing the speech signal for the voice recognition system such as Mel - Frequency Cepstrum Coefficients (MFCC). During the authentication phase the in put voice signal is recorded and processed comparing it by using MFCC features with a signal that has been previously stored in the database by the same user. The main purpose is to compare some of the main machine learning algorithms to classify them on t his particular application

• Publication Date: 03-Sep-2017
• DOI: 10.15224/978-1-63248-130-6-04
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