Speaker Identification Using K-means Method Based on Mel Frequency Cepstral Coefficients

Year: 2012

Issue: Feb-Apr   

Title: Speaker Identification Using K-means Method Based on Mel Frequency Cepstral Coefficients 

Author Name: Dirman Hanafi, Abdul Syafiq Abdul Sukor 

Synopsis: 

The most commonly method use by people to protect their secured data or information is using password or PIN/ID protection. This method require user to authenticate them by entering password that they had already created. However, due to lack of security the data is not secured enough. There are cases of fraud and theft when people can easily know the password. But as time goes by, there is a new technology known as Biometric Identification System. It uses biometric characteristics of an individual that is unique and different from everyone else and therefore can be use to authenticate the user authority access. This paper focused on an implementation of speech recognition as medium security access control to restricted services such as phone banking system, voicemail or access to database services. First, speaker signal will go to pre-treatment process, where it will remove the background noise. Then, features from speech signal will be extracted using Mel Frequency Cepstrum Coefficients (MFCC) method. Then, using Vector Quantization, the features will be matched with the reference speech in database. The real speaker is identified by clustering the speech signal from the tested speaker to codebook of each speaker using K-means algorithm and the speaker with the lowest distortion Euclidean distances is chose as the correct speaker. The main focus of this research is speaker identification, which compared speech signal from unknown speaker to a database of known speaker using text-dependent utterances. From the experimental results shows that the method developed is able to recognize the correct voice source perfectly.