Similarity Measurement for Speaker Identification Using Frequency of Vector Pairs
Similarity measurement is an important part of speaker identification. This study has modified the similarity measurement technique performed in previous studies. Previous studies used the sum of the smallest distance between the input vectors and the codebook vectors of a particular speaker. In thi...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | EJournal Article |
| Published: |
Institute of Advanced Engineering and Science,
2014-08-01.
|
| Subjects: | |
| Online Access: | Get fulltext |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| LEADER | 02304 am a22003133u 4500 | ||
|---|---|---|---|
| 001 | ijeecs3740_2036 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Permana, Inggih |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Buono, Agus |e author |
| 700 | 1 | 0 | |a Silalahi, Bib Paruhum |e author |
| 245 | 0 | 0 | |a Similarity Measurement for Speaker Identification Using Frequency of Vector Pairs |
| 260 | |b Institute of Advanced Engineering and Science, |c 2014-08-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3740 | ||
| 520 | |a Similarity measurement is an important part of speaker identification. This study has modified the similarity measurement technique performed in previous studies. Previous studies used the sum of the smallest distance between the input vectors and the codebook vectors of a particular speaker. In this study, the technique has been modified by selecting a particular speaker codebook which has the highest frequency of vector pairs. Vector pair in this case is the smallest distance between the input vector and the vector in the codebook. This study used Mel Frequency Cepstral Coefficient (MFCC) as feature extraction, Self Organizing Map (SOM) as codebook maker and Euclidean as a measure of distance. The experimental results showed that the similarity measuring techniques proposed can improve the accuracy of speaker identification. In the MFCC coefficients 13, 15 and 20 the average accuracy of identification respectively increased as much as 0.61%, 0.98% and 1.27%. | ||
| 540 | |a Copyright (c) 2014 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc-nd/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Computer Engineering | ||
| 690 | |a Frequency of Vector Pairs, MFCC, Similarity Measurement; SOM; Speaker Identification | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 12, No 8: August 2014; 6205-6210 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v12.i8 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3740/2036 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3740/2036 |z Get fulltext |