کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1101677 953574 2014 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Classification of Vocal Aging Using Parameters Extracted From the Glottal Signal
ترجمه فارسی عنوان
طبقه بندی پیری آوایی با استفاده از پارامترهای استخراج شده از سیگنال گلوتل
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی بیماری های گوش و جراحی پلاستیک صورت
چکیده انگلیسی

SummaryThis article proposes and evaluates a method to classify vocal aging using artificial neural network (ANN) and support vector machine (SVM), using the parameters extracted from the speech signal as inputs. For each recorded speech, from a corpus of male and female speakers of different ages, the corresponding glottal signal is obtained using an inverse filtering algorithm. The Mel Frequency Cepstrum Coefficients (MFCC) also extracted from the voice signal and the features extracted from the glottal signal are supplied to an ANN and an SVM with a previous selection. The selection is performed by a wrapper approach of the most relevant parameters. Three groups are considered for the aging-voice classification: young (aged 15–30 years), adult (aged 31–60 years), and senior (aged 61–90 years). The results are compared using different possibilities: with only the parameters extracted from the glottal signal, with only the MFCC, and with a combination of both. The results demonstrate that the best classification rate is obtained using the glottal signal features, which is a novel result and the main contribution of this article.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Voice - Volume 28, Issue 5, September 2014, Pages 532–537
نویسندگان
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