Objective Gender and Age Recognition from Speech Sentences

Faek, Fatima (2015) Objective Gender and Age Recognition from Speech Sentences. Aro, The Scientific Journal of Koya University, 3 (2). pp. 24-29. ISSN 24109355

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Official URL: http://dx.doi.org/10.14500/aro.10072


In this work, an automatic gender and age recognizer from speech is investigated. The relevant features to gender recognition are selected from the first four formant frequencies and twelve MFCCs and feed the SVM classifier. While the relevant features to age has been used with k-NN classifier for the age recognizer model, using MATLAB as a simulation tool. A special selection of robust features is used in this work to improve the results of the gender and age classifiers based on the frequency range that the feature represents. The gender and age classification algorithms are evaluated using 114 (clean and noisy) speech samples uttered in Kurdish language. The model of two classes (adult males and adult females) gender recognition, reached 96% recognition accuracy. While for three categories classification (adult males, adult females, and children), the model achieved 94% recognition accuracy. For the age recognition model, seven groups according to their ages are categorized. The model performance after selecting the relevant features to age achieved 75.3%. For further improvement a de-noising technique is used with the noisy speech signals, followed by selecting the proper features that are affected by the de-noising process and result in 81.44% recognition accuracy.

Item Type: Article
Uncontrolled Keywords: Age classification from speech, gender classification from speech, MFCC based gender and age recognition, SVM classifier.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: ARO-The Scientific Journal of Koya University > VOL 3, NO 2 (2015)
Depositing User: Dr Salah Ismaeel Yahya
Date Deposited: 03 Aug 2017 20:07
Last Modified: 03 Aug 2017 20:07
URI: http://eprints.koyauniversity.org/id/eprint/60

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