A new framework based on KNN and DT for speech identification through emphatic letters in Moroccan dialect
Arabic dialects differ substantially from modern standard arabic and each other in terms of phonology, morphology, lexical choice and syntax. This makes the identification of dialects from speeches a very difficult task. In this paper, we introduce a speech recognition system that automatically iden...
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Institute of Advanced Engineering and Science,
2021-03-01.
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| LEADER | 02941 am a22003733u 4500 | ||
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| 001 | 0 nhttps:__ijeecs.iaescore.com_index.php_IJEECS_article_downloadSuppFile_22605_3183 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Mouaz, Bezoui |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Walid, Cherif |e author |
| 700 | 1 | 0 | |a Abderrahim, Beni-Hssane |e author |
| 700 | 1 | 0 | |a Abdelmajid, Elmoutaouakkil |e author |
| 245 | 0 | 0 | |a A new framework based on KNN and DT for speech identification through emphatic letters in Moroccan dialect |
| 260 | |b Institute of Advanced Engineering and Science, |c 2021-03-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/22605 | ||
| 520 | |a Arabic dialects differ substantially from modern standard arabic and each other in terms of phonology, morphology, lexical choice and syntax. This makes the identification of dialects from speeches a very difficult task. In this paper, we introduce a speech recognition system that automatically identifies the gender of speaker, the emphatic letter pronounced and also the diacritic of these emphatic letters given a sample of author's speeches. Firstly we examined the performance of the single case classifier hidden markov models (HMM) applied to the samples of our data corpus. Then we evaluated our proposed approach KNN-DT which is a hybridization of two classifiers namely decision trees (DT) and k-nearest neighbors (KNN). Both models are singularly applied directly to the data corpus to recognize the emphatic letter of the sound and to the diacritic and the gender of the speaker. This hybridization proved quite interesting; it improved the speech recognition accuracy by more than 10% compared to state-of-the-art approaches. | ||
| 540 | |a Copyright (c) 2021 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Computer Science | ||
| 690 | |a Decision tree; Hidden markov model; K-nearest neighbor; Machine learning; 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 21, No 3: March 2021; 1417-1423 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v21.i3 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/22605/14713 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/downloadSuppFile/22605/3182 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/downloadSuppFile/22605/3183 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/22605/14713 |z Get fulltext |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/downloadSuppFile/22605/3182 |z Get fulltext |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/downloadSuppFile/22605/3183 |z Get fulltext |