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Speaker Identification system using Mel Frequency Cepstral Coefficient and GMM technique
| Content Provider | Semantic Scholar |
|---|---|
| Author | Prabhakar, Om Prakash Sahu, Navneet Kumar |
| Copyright Year | 2013 |
| Abstract | The performance of speech recognition systems have improved due to recent advances in speech processing technique but there is still need of improvement. In this paper we present the hybrid approach for feature extraction technique using MFCC & LPC, two classification techniques, Gaussian mixture models (GMM) and Vector quantization (VQ) with LBG design algorithm are used for classification of speakers.The Vector Quantization (VQ) approach is used for mapping vectors from a large vector space to a finite number of regions in that space. Each region is called a cluster and can be represented by its center called a codeword. The collection of all codewords is called a codebook. After the enrolment session, the acoustic vectors extracted from input speech of a speaker provide a set of training vectors. LBG algorithm due to Linde, Buzo and Gray is used for clustering a set of L training vectors into a set of M codebook vectors. For comparison purpose, the distance between each test codeword and each codeword in the master codebook is computed. The difference is used to make recognition decision. The entire coding was done in MATLAB and the system was tested for its reliability. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://iosrjournals.org/iosr-jeee/Papers/ICAET-2014/electronics/volume-4/12.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
